In the history of high-performance polymer composite parts with continuous in-plane fibre reinforcement, the comparatively moderate structural-mechanical properties in their out-of- plane-z-direction and the limited load carrying capability between individual reinforcement layers within the laminated structures have always been one of the greatest challenges. Plenty of research work has been carried out to improve load transfer capability as well as fracture toughness for crack opening events between the reinforcement layers by means of out-of-plane fibre reinforcement implementation, for example by sewing or z-pinning technologies. However, the results have not become established across a wide range of applications so far, because the technologies used have led to considerable losses of in-plane strength properties. In this paper first results are presented for a new method of a low fraction z-fibre reinforcement by means of very thin diameter laser drilled holes filled with short carbon fibres, demonstrating potential to improve Mode II fracture toughness.

Background: Nutritional status and oxidative stress have been implicated in the pathogenesis and persistence of long COVID, but data in patients undergoing hemodialysis (HD) are limited. The present study aimed to investigate the association between pre-infection nutritional status, oxidative stress, and one-year long COVID persistence in HD patients. Methods: This prospective observational cohort study enrolled 115 HD patients with confirmed COVID-19. Nutritional status was assessed using the Controlling Nutritional Status (CONUT) score twice: before infection and three months post-infection. Oxidative markers included malondialdehyde (MDAs), ceruloplasmin, transferrin, and sulfhydryl groups. The endpoint was one-year long COVID persistence. Results: Moderate pre-infection CONUT scores were associated with heightened severe undernutrition risk (p < 0.0001), elevated MDAs (p < 0.0001), and reduced ceruloplasmin levels (p = 0.0009) at three months post-COVID-19 compared to light CONUT scores. Pre-infection CONUT score independently predicted post-COVID oxidative damage [OR 2.3 (95%CI 1.2; 4.6), p < 0.0001] and one-year long COVID persistence [HR 4.6 (95%CI 1.4; 9.9), p < 0.0001], even after adjusting for potential confounders. Conclusion: Moderate pre-infection undernutrition in patients undergoing HD associated with increased post-COVID oxidative stress intensity and heightened risk of one-year long COVID persistence.

BACKGROUND AND AIMS: Cardiovascular disease and colorectal cancer (CRC) are significant health problems and share some risk factors. The aim of our study was to develop and validate a predictive score for advanced colorectal neoplasia (CRN) based on risk factors for cardiovascular disease and CRC. MATERIALS AND METHODS: A cross-sectional study comprising a derivation cohort and an external validation cohort of 1049 and 308 patients respectively. A prediction score for advanced CRN (CRNAS: Colorectal Neoplasia Advanced Score) was developed from a logistic regression model, comprising sex, age, first-degree family history for CRC, systolic and diastolic blood pressure, total cholesterol, HDL-cholesterol, body mass index, diabetes, smoking, and antihypertensive treatment. Other cardiovascular risk scores (Framingham-Wilson, REGICOR, SCORE and FRESCO) were also used to predict the risk of advanced CRN. The discriminatory capacity of each score was evaluated using the area under the curve (AUC). RESULTS: CRN were found in 379 subjects from the derivation cohort (36%) including 228 patients (22%) with an advanced CRN. Male sex, age, diabetes, and smoking were identified as independent risk factors for advanced CRN. The newly created score (CRNAS), showed an AUC of 0.68 (95% CI: 0.64-0.73) for advanced CRN, which was better than cardiovascular risk scores (p

This research explores the behaviors of Generation Z consumers in China, particularly focusing on their interaction with companies through social media for the joint creation of value. Adopting a qualitative methodology, the research initially constructs a scale for assessing co-creation of value on social media platforms. Subsequently, it delves into the motivational aspects of users' engagement in these co-creative activities. The study unveils a range of utilitarian and hedonic motivations that drive Generation Z's value co-creation actions on social media. Insights derived from the findings offer both theoretical and practical implications for the field.

Sample size using prevalence has been one of the most important medical research methodologies and has been used in original articles more often than any other statistical tool available. The simple formula consists of variables interdependent and it is as important to understand how they influence each other as it is to learn to use the formula to calculate the sample size. With the choice of different amounts of precision and levels of confidence available to a medical researcher, it should be of paramount importance to understand what a slight change in choosing the parameter would mean at the end of the research. Understanding of different Z values, Levels of precision, and ranging Prevalence is required to understand the effect on the sample size and subsequently on the research. Topological representation using parameter ranges can be used to demonstrate this relationship.

Background/Objectives: Endometriosis represents substantial direct and indirect healthcare costs impacted by absent accurate, non-invasive uniformly diagnostic tools. We endeavored to demonstrate gastrointestinal myoelectrical activity (GIMA) biomarkers unique to endometriosis allow noninvasive, uniformly accurate diagnosis or exclusion of endometriosis. Methods: Prospective open-label comparative study of 154 patients, age >18, with or without diagnosed endometriosis. Population included 62 non-endometriosis controls (Cohort 1), 43 subjects with surgically histologically-confirmed endometriosis (Cohort 2), and 49 subjects with abdominal pain and negative imaging (Cohort 3). Electroviscerography (EVG) recorded GIMA biomarkers from three abdominal electrodes before and 30-minutes post water-load protocol. Cohort 2 had postoperative EVG and Cohort 3 had preoperative EVG. Calculated specificity, sensitivity, NPV, PPV and predictive probability or C-Statistic used univariate, multivariate, linear and logistical regression analyses of the area under the curve (AUC) at all frequency and time points, including age and pain covariants. Results: Non-endometriosis cohort differed significantly from endometriosis cohorts (p<0.001) for median (IQR), and AUC percent frequency distribution of power at baseline, 10-minute, 20-minute, and 30-minute post water-load at all frequency ranges 15-20cpm, 30-40cpm and 40-50cpm. Endometriosis cohorts were statistically similar (p>0.05). GIMA biomarker threshold scoring demonstrated 95%/91% sensitivity and PPV, 96%/95% specificity and NPV and C-statistic of >99%/98% respectively for age subsets. GIMA biomarkers in Cohort 3 predicted 47/49 subjects positive and 2/49 negative for endometriosis, confirmed surgically. Hormonal therapy, surgical stage, nor pain score affected diagnostic accuracy. Conclusions: Non-invasive electroviscerography with GIMA biomarker detection distinguished participants with and without endometriosis based upon endometriosis specific GIMA biomarkers threshold scoring.

The objective of this study is to determine the relationship between body condition score (BCS) and body carcass fat (BCF) of ewes at two key stages of the production cycle. Data were collected from 88 Coopworth ewes including BCS measurements manually evaluated by the farm manager, BCF measurements determined by computerized tomography (CT) and body parameter measurements automatically determined by an image processing application. Artificial neural network (ANN) statistical analysis method was used to develop a relationship between the body parameters and the BCF with an r2=0.96 and RMSE=1.01 using all top and side variables.

We demonstrate how a rigorous mathematical approach can be used to extract a current CMB temperature of 2.7276 ±0.0723 K from the 580 type Ia supernova data points in the Union2 database. Using redshift formula: z = Sqrt(Rh/R_t) − 1, incorporated into our new CMB redshift prediction redshift formula, we find that the above current CMB temperature value is a remarkably good match for this particular data set. In addition, we can alternatively start out with the measured current CMB temperature and extract the Hubble constant from all 580 supernovae. We then get an estimated Hubble constant of H0 = 66.8711+0.0019 km/s/Mpc when using the CMB temperature from the recent Dhal et al study [1] in combination with redshifts from all 580 supernovae. Furthermore, we get an estimated Hubble constant value of H_0 = 66.8943+0.0287 km/s/Mpc when using the CMB temperature measured by Fixsen [2]. In summary, our simple model essentially perfectly matches all 580 type Ia supernova redshifts while extracting H_0 or T_0 values. The Hubble constant we extract by this method fits very well with the Hubble constant extracted from the CMB by other studies. We believe that our new approach likely solves the Hubble tension problem, at least inside R_h = ct cosmology.

(1) Background: BRCA mutation and homologous recombination deficiency (HRD) are used to administrate PARP inhibitors (PARPi) maintenance therapy. It is known that PARPi efficacy is related to platinum sensitivity and that the latter can be demonstrated from the CA-125 elimination rate constant (KELIM). This study aims to investigate if KELIM can be another tool in the identification of patients that could be benefit from PARPi therapy.; (2) Methods: Retrospective analysis of patients with high-grade serous advanced ovarian cancer that underwent cytoreduction and was further tested for HRD status. The HRD status was tested either by myChoice HRD CDx assay or by RediScore assay. KELIM score was measured in both neoadjuvant and adjuvant settings with the online tool biomarker-kinetics.org.; (3) Results: Thirty-nine patients had available data for estimating both HRD status and KELIM score. When assuming KELIM as a binary index test with the value 1 as the cut-off point, the sensitivity was 0.86, 95% CI (0.64-0.97), and the specificity 0.83, 95% CI (0.59-0.96). On the other hand, when assuming KELIM as a continuous index test, the AUC was 81% and the optimal threshold, using the Youden index, was identified as 1.03 with a sensitivity of 85.7% and a specificity of 83.3%; (4) Conclusions: KELIM score seems to be a new, cheaper and faster tool to identify patients that can benefit from PARPi maintenance therapy.

This study aimed to introduce a novel machine learning (ML) model designed to predict the need of interventions during endoscopy in patients with upper gastrointestinal bleeding (UGIB). The risk stratification tools in current use, such as the Glasgow Blatchford Score (GBS) and pre-endoscopic Rockall score, have limitations in accurately predicting the need for endoscopic interventions. All patients diagnosed with UGIB from January 2013 to October 2023 who underwent endoscopy were included in the study. Variables extracted included demographics, social history ,clinical history, clinical presentation and symptoms, drug history, management prior to endoscopy, findings during endoscopy, laboratory variables and vitals, and post-endoscopic results. Three machine learning models including Random Forest Classifier (RFC), Gradient Boosting Classifier (GBC), and AdaBoost Classifier were used to evaluate the need for intervention during endoscopy in our study. A total of 1372 patients were included from three major hospitals in Jordan, of whom 242 underwent endoscopic intervention. The GBC outperformed all other models and pre-endoscopic scores in predicting the need for endoscopic intervention with an area under the curve of 0.861. Findings during endoscopy, platelet count, pulse rate and systolic blood pressure during admission were the most contributing features in predicting the need for the need of endoscopic intervention. This study highlights the potential of machine learning models in enhancing decision making for UGIB management.

Abstract. Introduction: BMD study gives partial information on bone health in patients with TSH suppression therapy due to Differentiated Thyroid Cancer (DTC). TBS, a new parameter of bone microarchitecture is propose for bone quality study. This study analyze their long-term use in patients with DTC. Methods: BMD was measured by DXA and TBS with iNsigth software in 145 postmenopausal DTC patients. Vertebral Fractures (VFs) with a semi-quantitative x-ray method. Results: BMD at the end study was not different from initial. TBS decreased from 1.35±0.1 to 1.27±0.1 (p=0.002). PTH, Osteocalcin, and BAP were increased, suggesting increased bone remodeling. There was an increase in osteoporosis and osteopenia (40.6% and 16.5% to 46.6% and 18.6%); 31% had partially degraded and 15.1% degraded TBS changed to 48,9% and 24,8% at the end study. VFs in 30 patients, was not different in age, BMI, calcium and alcohol ingestion, smoking, radioiodine, or thyroid parameters vs. without VFs. Odds ratio for VFs increased with osteopenia (OR 2.63). Combination of TBS plus TBS did not improve discrimination. Conclusions: TBS was lowered while BMD did not differ. Percentage of osteoporosis and osteopenia and of partially degraded and degraded TBS was higher at the end study. Predominant discordance rate was found in partially degraded microarchitecture, in which the proportion of osteopenia was higher than normal or osteoporotic patients. AUC of TBS plus BMD did not improve discrimination. TBS, radioactive iodine, and sedentary lifestyle were the main differential data for patients with DTC and VFs.

Background and Objectives: ARNE score was developed for the prediction of difficult airway for both general and ENT surgery with a universal cut-off value. We tested the accuracy of this score in the case of laryngeal surgery and provided an insight of its combination with flexible laryngoscopy. Materials and Methods: This prospective pilot clinical study included 100 patients who were being scheduled for microscopic laryngeal surgery. We have calculated ARNE score for every patient and flexible laryngoscopy was provided preoperative. Difficult intubation was assessed according to intubation difficulty score (IDS). Results: A total of 33% patients had difficult intubation according to IDS. ARNE score showed to be accurate for prediction of difficult intubation in laryngology with P<0.0001 and AUC 0.784. Flexible laryngoscopy showed to be an independent parameter with P<0.0001 and AUC 0.766. We have defined a new cut-off value of 15.50 for laryngology, according to AUC curve. After the patients were divided in two groups, according to the new cut-off value and provided cut-off value, AUC improved to 0.707 from 0.619 respectively. Flexible laryngoscopy improved the prediction model of ARNE score to AUC 0.882 and of new cut-off value to AUC 0.833. Conclusions: It is recommended to use flexible laryngoscopy together with ARNE score in difficult airway prediction in patients with laryngeal pathology. Also, universally recommended cut-off value of 11 can not be effectively used in laryngology and a new cut-off value of 15.50 is recommended.

With the use of linear regression modeling, this study sought to forecast and analyze rainfall patterns in Ethiopia. The dataset included historical rainfall data as well as pertinent independent variables. The R-squared score and mean squared error (MSE) were used to assess the effectiveness of the linear regression model. The results showed that the model's ability to forecast and analyze rainfall patterns was not very good. Only around 5.3% of the variance in rainfall could be explained by the chosen independent variables, according to the R-squared score of 0.053. This low number indicated that there was little correlation between the selected variables and rainfall, and that a sizable percentage of the variation in the dependent variable was not captured by the model. The model's accuracy in forecasting rainfall was shown to be quite low by the MSE error, with significant squared discrepancies between the expected and actual amounts. These results support the notion that the linear regression model as it is now designed is not appropriate for studying or forecasting Ethiopia's rainfall patterns. Alternative modeling approaches, the inclusion of other pertinent factors, and the assurance of the availability of high-quality data that faithfully captures the intricate dynamics of rainfall in the area all require more investigation.

The global textile sector, pivotal to economic development, significantly contributes to environmental degradation, prompting a shift towards sustainable raw material sources. Embracing circular economy principles, this industry is exploring the valorization of agricultural by-products. This study introduces an innovative approach to repurposing mango waste into valuable textile fibers, a byproduct of the fruit processing industry, predominantly generated during juice and jam production. The focus is on the lignocellulosic constituents of mango waste, specifically the peel, seed, and fibrous material, traditionally considered as refuse. Previous research has predominantly utilized mango peel in pectin extraction for food applications, whereas the potential of seed and fibrous content remains underexplored. This investigation endeavors to transform these fibrous by-products into high-value materials suitable for textile manufacturing. The process involved washing, drying, and comprehensive physicochemical characterization of mango fibers, emphasizing lignin quantification, revealing a composition of 12.2% lignin. An experimental design was employed to elucidate the impact of variables such as liquid-to-solid ratio, reaction duration, and sodium hydroxide concentration on lignin dissolution through alkaline hydrolysis. Optimal conditions—10% NaOH concentration, 30 mL/g liquid-to-solid ratio over six hours—achieved an 83% reduction in lignin content. The resulting fibers exhibited properties akin to conventional natural fibers, including a favorable aspect ratio indicative of their suitability for textile applications. A subsequent softening process using propylene glycol enhanced the fibers' spinability, producing a durable, textured fabric ideal for eco-conscious fashion applications, including bags, footwear, and accessories. This research demonstrates the feasibility of converting mango waste into a textile-worthy material and underscores the importance of waste revalorization in promoting sustainability within the circular economy framework.

Locoregional anaesthetic techniques are invaluable for providing multimodal analgesia for painful surgical procedures. This prospective, randomised study describes a nerve stimulator-guided bra-chial plexus blockade (BPB) in rabbits undergoing orthopaedic surgery in comparison to systemic lidocaine. Premedication was provided with intramuscular (IM) medetomidine, fentanyl and midazolam. Anaesthesia was induced (propofol IV) and maintained with isoflurane. Nine rabbits received a lidocaine BPB (2%; 0.3 ml kg-1), and eight received lidocaine constant rate infusion (CRI) (2 mg kg-1 IV, followed by 100 µg kg-1 minute-1). Rescue analgesia was provided with Fentanyl IV. Carprofen was administered at the end of surgery. Post-operative pain was determined using the Rabbit Grimace Scale (RGS) and a composite pain scale. Buprenorphine was administered accord-ing to pain score for two hours after extubation. Rabbits were filmed during the first two hours to measure distance travelled and behaviours. Food intake and faeces output were compared. Every rabbit in CRI required intraoperative rescue analgesia compared to no rabbits in BPB. How-ever, rabbits in both groups had similar pain scores and there was no difference in administration of postoperative analgesia. There were no significant differences in food intake or faeces produc-tion over 18 hours, and no significant differences in distance travelled, or behaviours examined during the first two hours. BPB seems superior for intraoperative analgesia. Postoperatively both groups were comparable.

The purpose of this study is to examine the match-related performance (scores and penalties) of the athletes in the Junior EJC (European Judo Championship) and U23 EJC categories before and immediately after the Covid-19 quarantine, according to gender and weight category groups. Our sample was based on the junior and U23, male and females, 2019-2020 Junior European Judo Championships and 2019-2020 U23 European Judo Championships. A total of 1431 matches in these tournaments were analyzed: male (n=812) and female (n=619). The main findings of this study showed that most matches in both the male and female categories resulted in ippon (2019-2020 average: 64,35% for Junior male, 70,55% for U23 male and 69,3% for Junior female, 64,4% for U23 female). No significant differences (p > 0.05) were observed between gender and age groups concerning the match scores. In the formation phase of the technique, considerations of high- and low-intensity actions, and analysis of the speed of athletes during matches in official competitions can help to better understand the dynamics of the variability of movements in judo matches. In addition, suggestions are presented to be applied to athletes in different age categories who are on the way to become Olympic athletes.

Extensive genome structure variation, such as copy number variations (CNVs) and presence/absence variations, is the basis for the remarkable maize genetic diversity; however, the effect of CNVs on maize herbivory defense remains largely underexplored. Here, we report that the naturally occurring duplication of the maize 9-lipoxygenase gene, ZmLOX5, leads to increased resistance of maize to herbivory by fall armyworms (FAW). Previously, we showed that ZmLOX5-derived oxylipins are required for defense against chewing insect herbivores and identified several inbred lines, including Yu796, that contained duplicated CNVs of ZmLOX5, referred to as Yu796-2×LOX5. To test whether introgression of the Yu796-2×LOX5 locus into the herbivore-susceptible B73 background that contains a single ZmLOX5 gene is a feasible approach to increase resistance, we generated a series of near-isogenic lines that contained either 2, 1 or 0 copies of the Yu796-2×LOX5 locus in the B73 background by six back crosses (BC6). Droplet digital PCR (ddPCR) confirmed the successful introgression of the Yu796-2×LOX5 locus in B73. The resulting B73-2×LOX5 inbred line displayed increased resistance against FAW associated with increased expression of ZmLOX5, increased wound-induced production of its primary oxylipin product, the α-ketol, 9-hydroxy-10-oxo-12(Z),15(Z)-octadecadienoic acid (9,10-KODA), and the downstream defense hormones regulated by this molecule, 12-oxo-phytodienoic acid (12-OPDA) and abscisic acid (ABA). Surprisingly, wound-induced JA-Ile production was not increased in B73-2×LOX5, resulting from the increased JA catabolism. Furthermore, B73-2×LOX5 displayed enhanced drought tolerance likely due to increased ABA and 12-OPDA content. Taken together, this study revealed that the duplicated CNV of ZmLOX5 quantitively contributes to maize antiherbivore defense and presents proof-of-concept evidence that the introgression of naturally occurring duplicated CNVs of a defensive gene into the productive, but susceptible, crop varieties is a feasible breeding approach for enhancing plant resistance to herbivory and tolerance to abiotic stress.

This retrospective study aimed to compare risk factors for vascular calcification (VC) between pre-hemodialysis (HD) and prevalent HD adult patients while investigating associations with calcification biomarkers. Baseline data from 30 pre-HD and 85 HD patients were analyzed, in-cluding iPTH, vitamin D, FGF-23, fetuin-A, sclerostin and VC scores (Adragao method). Preva-lence of VC was similar in both groups, but HD patients had more frequent VC scores ≥6. Pre-HD patients were older, with higher prevalence of hypertension and less frequent use of calcium phosphate binders. Both groups showed similar patterns of hyperphosphatemia, low vitamin D, and iPTH. Fetuin-A levels were higher in pre-HD, while FGF-23 was elevated in HD patients. Higher VC risk in pre-HD patients was associated with male gender, older age, lower fetuin-A and higher sclerostin, lower ferritin and no vitamin D treatment, while in HD patients with higher sclerostin, FGF23 and urea, and lower iPTH. Conclusion. Progression of CKD from the pre-HD to the HD stage is accompanied by a decreased effect of the inhibitor and an increase in the promoter VC. However, mineral imbalance, hormonal regulation, treatment options, and patient-specific fac-tors should be considered. Further studies are needed to elucidate the underlying pathways.

Plant viral nanoparticles (VNPs) are attractive to researchers in nanomedicine due to their safety, easy production, resistance, and straightforward functionalization. In this paper, we developed and successfully purified a VNP derived from turnip mosaic virus (TuMV), a well-known plant pathogen, that exhibits high affinity for immunoglobulins G (IgG) thanks to its functionalization with the Z domain from staphylococcal protein A via gene fusion. We selected cetuximab as a model IgG to prove the versatility of this novel TuMV VNP by developing a fluorescent nanoplatform to mark tumoral cells of the line Cal33, from tongue squamous cell carcinoma. We observed that the fluorescent VNP-cetuximab bound selectively to Cal33 and were internalized by confocal microscopy, revealing the potential of this nanotool in cancer research.

Background: Diabetes mellitus (DM) and osteoporosis are two of the most widespread metabolic disease in the world. The aim of this study is to investigate the prevalence of DM among patients affected by osteoporosis and fragility fractures, and to search differences in clinical features. Methods: 713 patients belonging to CTO Bone Unit because of osteoporosis and fragility fractures were divided into two groups, according to the diagnosis of DM. The clinical and bone characteristics of patients were compared. Results: Prevalence of DM was 10.8%. When compared to patients without DM, the median age at the time of first fracture was similar (72 years ± 14 IQR vs 71 years ± 12 IQR); prevalence of combination of vertebral and hip fractures was higher (p=0.039), as well as prevalence of males, although not significantly (p=0.051). Bone mineral density (BMD) at all sites was higher in DM group; Trabecular Bone Score (TBS), instead, was significantly lower (p<0.001). Conclusions: Patients with fragility fractures and DM more frequently show combination of major fractures with higher BMD levels. In these patients, TBS could be a better indicator of bone health than BMD and therefore should be used as a diagnostic tool in clinical practice.

In the current work, the stable queueuing system's Generalised Z-Entropy (GZE) of Rényian formalism is examined in its fractal dimension. Notably, fractal dimension’s resulting behaviour that corresponds to the GZE parameters is examined through numerical tests. This research makes a substantial generalization in the literature by fusing fractal geometry and information theory to shed light on how entropy and complexity interact. More fundamentally, the significant role of fractal dimension to advance Big Data Analytics(BDAs) is highlighted. Closing remarks combined with open problems and the next phase of research are provided.

Using the h-index to assess individual researchers is not only unethical and unfair but also inaccurate and misleading. This index fails to offer a reliable measure of a researcher's impact based on their citation scores. Beyond statistical and conceptual considerations, authorship practices, especially in the case of multi-authored publications, give rise to significant problems that often go unnoticed. While some modifications of the h-index have been proposed to mitigate these weaknesses, the fundamental deficiencies persist. Most of these flaws have been effectively addressed by the c-score, a composite citation index. The c-score excludes self-citations, normalizes the number of citations by considering the number of authors in each paper, and takes into account first, single, and last authorship. This approach provides a more realistic measure of the impact of each individual researcher based on raw citations.

This study presents a novel approach for automating the body condition scoring of dairy cows, leveraging advancements in 3D imaging technology and deep neural networks. The primary objective was to design and implement a system capable of accurately and efficiently assessing the body condition of dairy cows, a critical metric in livestock management for optimizing health and productivity. To achieve this, a 3D camera was employed to capture detailed point cloud data, reconstructing the three-dimensional morphology of individual cows. The obtained data were then fed into a deep neural network, specifically tailored for the task of ranking body condition. The neural network was trained on a diverse dataset of annotated body condition score representing varying degrees of body condition, ensuring robust performance across different physiological states. The results demonstrate the efficacy of the proposed system in automatically and objectively scoring the body condition of dairy cows. The automated process not only expedites the assessment but also reduces the subjectivity associated with manual scoring methods. This innovative approach holds promise for improving the efficiency of dairy farm management by providing timely and accurate body condition assessments. The integration of 3D imaging and deep learning techniques paves the way for future advancements in precision livestock farming, contributing to enhanced animal welfare, optimized production, and sustainable agriculture practices.

Background and aims: For many surgical procedures, spinal anesthesia is a reliable and efficient anesthetic approach. Numerous drugs have been reported to be administered to intrathecal local anesthetics as adjuvants to increase the efficacy of spinal anesthesia. There is little evidence of the effect of intrathecal dexmedetomidine on pain scores and the consumption of analgesia postoperatively. Methods: After obtaining ethical approval, demographical and clinical data of patients who underwent surgical procedures under spinal anesthesia with intrathecal dexmedetomidine or fentanyl was collected and analyzed. Results: In this study with 96 patients, intrathecal dexmedetomidine (group D) resulted in significantly lower post-operative pain scores compared to intrathecal fentanyl (group F) (p=0.000). Across various surgical types, including Orthopedic, General, Urology, and Obs/Gyne procedures, group D consistently displayed reduced pain scores (p<0.001). The number of patients who needed post-operative analgesia was significantly higher in group (F) than in group (D) (40 vs 23, p=0.002). Conclusion: Compared to fentanyl, intrathecal dexmedetomidine as an adjuvant to local anesthesia was found to lower post-operative pain scores and decrease the need for post-operative analgesia.

Anastomotic Leakage (AL) remains the main cause of post-esophagectomy morbidity and mortality. Early detection can avoid sepsis and reduce morbidity and mortality. This study evaluates the diagnostic accuracy of the NUn-score and its components as early detectors of AL. This single centre observational cohort study included all esophagectomies from 2010-2020. C-reactive Protein (CRP), Albumin (Alb) and White cell count (WCC) were analyzed and Nun-scores calculated. Area under the curves (AUC) were used to assess their predictive accuracy. Seventy-four of the 668 patients (11%) developed an AL. CRP and the NUn-score proved to be good diagnostic accuracy tests on POD2 (CRP AUC:0,859; Nun-score AUC:0,869) and POD4 (CRP AUC:0,924; Nun-score AUC:0,948). A 182mg/L CRP cut-off on POD4 yielded a 87% sensitivity, 88% specificity, a negative predictive value (NPV) of 98% and a positive predictive value (PPV) of 47,7%. A Nun score cut-off>10 resulted in 92% sensitivity, 95% specificity, 99% NPV and 68% PPV. Albumin and WCC have limited value in the detection of post-esophagectomy AL. Elevated CRP and a high NUn score on POD4 provide a high accuracy to predict AL after esophageal cancer surgery. Their high negative predictive value allows to select patients who can safely proceed with enhanced recovery protocols.

(1) Background: CTA has validated the use of pericoronary adipose tissue (PCAT) attenuation as a credible indicator of coronary inflammation and plays a crucial role in coronary artery disease (CAD). This study aimed to evaluate the long-term effects of high-dose statins on PCAT attenuation at coronary lesion sites and changes in plaque distribution; (2) Methods: Our prospective observational study included 52 patients (mean age 60.43) with typical chest pain, a low-to-intermediate likelihood of CAD, and documented atheromatous plaque through CCT. We utilized advanced features of the CaRi-Heart® and syngo.via Frontier® systems to assess coronary plaques and changes in PCAT attenuation; (3) Results: Changes in plaque morphology were investigated, revealing significant alterations. Notably, in mixed plaques, calcified portions increased (p < 0.0001), while non-calcified plaque volume (NCPV) decreased (p = 0.0209). PCAT attenuation generally decreased after one year and remained low, indicating reduced inflammation in the following arteries: LAD (p = 0.0142), LCX (p = 0.0513), and RCA (p = 0.1249). The CaRi-Heart® risk also decreased significantly (p = 0.0041). Linear regression analysis demonstrated a correlation between increased PCAT attenuation and higher volumes of NCPV (p < 0.0001, r = 0.3032) and lipid-rich plaque volume (p < 0.0001, r = 0.3281); (4) Conclusions: Our study provides evidence that high-dose statin therapy significantly reduces CAD risk factors, inflammation, and plaque vulnerability, as evidenced by the notable decrease in PCAT attenuation, a critical indicator of plaque progression.

Recently, Shehata et al. [37] introduced the r+1Rs(B;C; z) matrix function and established some properties. The aim of this study established to devote and derive certain basic properties including analytic properties, recurrence matrix relations, dierential properties, new integral representations, k- Beta transform, Laplace transform, fractional k-Fourier transform, fractional integral properties, the k-Riemann{Liouville and k-Weyl fractional integral and derivative operators an extended version of r+1Rs;k matrix function. We establish its relationships with other well known special matrix functions which have some particular cases in the context of three parametric Mittag-Leer matrix function, k- Konhauser and k-Laguerre matrix polynomials. Finally, some special cases of the established formulas are also discussed.

A number of epidemiological studies have implicated elevated iron levels with higher risks of cardiometabolic diseases, including the metabolic syndrome (MetS). MetS is a pathologic clustering of metabolic derangements characterized by central obesity, insulin resistance, hypertension, and dyslipidemia, which can all lead to increased cardiovascular disease morbidity and mortality. However, it remains unclear whether a causal association exists between higher iron status and MetS and its associated risk components. Using the data from the Taiwan Biobank (TWB) (19,012 males; 42,340 females) and of the European Whites from the UK Biobank (UKB) (128,549 males; 142,817 females), we first constructed ethnic- and sex-specific hemoglobin-polygenic risk scores (Hb-PRS) as instrumental variable (IV) for iron status with the Hb-associated SNPs we previously identified from genome-wide association studies (GWAS). We then conducted Mendelian randomization (MR) analyses to elucidate the causal role of elevated iron (either Hb-PRS quintiles or continuous Hb-PRS) on various metabolic components. MR-Egger regressions determined the potential pleiotropic effects of the constructed Hb-PRSs, while the causal relationship of Hb-PRS with anemia served as a control in the analyses. The mean Hb concentration range corresponding to the Hb-PRS quintiles is relatively narrow in both UKB (14.91-15.21 g/dL for males and 13.39-13.71 g/dL for females) and TWB (14.79-15.28 g/dL for males and 12.78-13.21 g/dL for females). In these windows of Hb-PRSs, we found differential associations of Hb-PRS with diabetes (T2D) or hyperglycemia (HGY) as compared to other MetS components. The highest quintiles of Hb-PRSs were causally associated with greater risks of hypertension (HTN) and hypertriglyceridemia (DLP) (i.e., [Taiwanese HC males: Q5 vs. Q1 ORHTN = 1.10 (1.00–1.21), p = 0.0473, Q4 vs. Q1 ORDLP = 1.10 (1.00–1.22), p = 0.0485; European White males: ORHTN = 1.05 (1.01–1.09), p = 0.0194, ORDLP = 1.04 (1.00–1.08), p = 0.0468]). Interestingly, we obtained a consistent negative causal association between increasing Hb-PRS quintiles and T2D or HGY risk across all sex subgroups (i.e., [Taiwanese HC females: ORHGY = 0.89 (0.84–0.95), 0.88 (0.83–0.94), 0.87 (0.82–0.93), 0.86 (0.81–0.92) from Q2 to Q5; European White females: ORHGY = 0.92 (0.87–0.98), 0.91 (0.86–0.97), 0.93 (0.87–0.98), 0.87 (0.82–0.93) from Q2 to Q5; all p < 0.05]. The positive causal relationships between Hb-PRSs and diastolic blood pressure (DBP) and triglycerides (TG) but inverse causal association with glucose (GLU) and glycated hemoglobin (HbA1c) further corroborated such findings. There is, however, a lack of causal association with central obesity (CO), while a U-shaped type of causality was observed for gout (GT) or hyperuricemia (HUA). Sensitivity analyses, which excluded subjects based on self-reports of health conditions or medications and hospital episode statistics data, revealed similar results. Our MR studies confirm a modest causal relationship between propensity of elevated iron status and increased risk of HTN and DLP. We have further observed that modestly lower iron levels causally contribute to the development of T2D. Further validation and elucidation of the underlying biological mechanisms are highly warranted.

Context and aim: Environmental awareness is the first step to climate change risk perceptions and environmental behaviour. However, this pathway is not always possible within different population segments and trust contexts. This study explores the conditional effect of trust on environmental behaviour in the Zed Generation in Albania. The consideration of the Zed generation due to two opposing traits, such as social courage and anti-social, make them an interesting topic to understand, especially for their importance in online communities. Method: The youth engagement environmental programme and the climate change risk perceptions framework are adopted in an input-output design. Environmental awareness (input) is the initiating factor, and climate change risk perception and community engagement as mediators of environmental behaviour(output). Individual and institutional trust is the moderating factor that inhibits/enhances engagement and environmental behaviour. Results: The moderation-mediation show that climate change risk perceptions did not mediate environmental behaviour. Environmental awareness directly affects it. However, low institutional trust inhibits the general trust that, in turn, lowers the impact of awareness in climate change perceptions and community engagement toward environmental protection. Practical recommendation: The application of the input-output model shows that the pathway that directly affects environmental behaviour among Zed Generation in Albania is not Climate change risk perception. In low-trust contexts, positive environmental behaviour can be generated through community engagement. Policymakers and educational programmes in low-middle-income countries might consider community engagement to mitigate trust issues and effectively deal with environmental problems with a global segment such as the Zed generation.

Intelligent Tutoring Systems (ITS) are increasingly popular for online learning. These systems use adaptive algorithms to recommend relevant content based on students' profiles. However, instructors need to periodically assess students' performance to ensure learning outcomes and adjust strategies accordingly. Our objective is to predict students' progress in advance, enabling teachers to make quicker decisions and facilitating the iterative process of adaptive algorithms. For this study, we collected a dataset from ALIN, an online learning platform, consisting of over 5,000 students' learning records and test results. Using this dataset, we conducted experiments employing various machine learning algorithms. The results indicate that learning behavior contributes to improving forecast performance, while students' progress strongly correlates with their previous test results. Additionally, we discovered that students' progress can be indirectly predicted by forecasting their scores. Furthermore, by breaking down overall scores into several distinct components and predicting individual scores for each component, the accuracy of the forecasts can be improved.

Background and Objectives: Cardiovascular events are the leading cause of morbidity and mortal-ity in hemodialysis (HD) patients. Identifying risk factors can help in the effort to reduce cardi-ovascular risk and improve life expectancy. The purpose of this study was to evaluate the ability of CHA2DS2-VASc score [risk index of stroke in atrial fibrillation (AF)] in patients with end stage kidney disease, to predict stroke, major cardiovascular events and mortality. Materials and Meth-ods: CHA2DS2-VASc and HAS-BLED (bleeding risk from use of anticoagulation in AF) scores were calculated in 237 HD patients, [99 women, median age 76 (15) years], at time they com-menced on HD. The scores’ ability to predict long term cardiovascular morbidity and mortality was estimated, both in those with and without AF. Results: CHA2DS2-VASc score was signifi-cantly increased in AF (n=69) compared to non-AF (n=168) patients, 5 (2.5) versus 4 (2), p<0.0001, respectively. Increased CHA2DS2-VASc score was associated with heart failure (p=0.007, p=0.024), stroke (p<0.0001, p<0.0001) and risk of all-cause mortality (p<0.0001, p<0.0001), in both groups, respectively. C statistics indicated that CHA2DS2-VASc score performed modest discrimination in this HD population with and without AF for heart failure, stroke, and all-cause mortality, but for cardiovascular mortality in AF group only. Conclusions: Increased CHA2DS2-VASc score at time starting on HD, can predict stroke, heart failure and all-cause mortality in HD patients in-dependent of the presence of AF. Risk of cardiovascular mortality could be predicted only on patients with AF.

This paper aims to contribute to refining the e-values for testing precise hypotheses, especially when dealing with nuisance parameters, leveraging the effectiveness of asymptotic expansions of the posterior. The proposed approach offers the advantage of bypassing the need for elicitation of priors and reference functions for the nuisance parameters and the multidimensional integration step. For this purpose, starting from a Laplace approximation, a posterior distribution for the parameter of interest only is considered and then a suitable objective matching prior is introduced, ensuring that the posterior mode aligns with an equivariant frequentist estimator. Consequently, both Highest Probability Density credible sets and the e-value remain invariant. Some targeted and challenging examples are discussed.

Posttraumatic stress disorder (PTSD) and/or specific PTSD symptoms may evoke disordered eating and unhealthy lifestyles, resulting in adverse cardiometabolic events (e.g., hypertension and obesity) in certain groups, which may implicate the treatment of this complex condition. The diagnostic criteria of PTSD have lately expanded beyond the three common symptoms (intrusion, avoidance, and hyperarousal). Simultaneously, four-, five-, and six-dimensional structures of the Impact of Event Scale-Revised (IES-R), a popular PTSD measure, seem to be more robust than the original three-dimension structure. Within the context of COVID-19, this instrumental study used a convenience sample of 58 dental healthcare workers (HCWs) from Russia (mean age = 44.1±12.2 years, 82.8% females) to examine the criterion and predictive validity of two IES-R structures: the IES-R3 and the IES-R6 (with the added symptoms of numbing, sleep disturbance, and irritability). The subscales of the two IES-R structures expressed good internal consistency, strong correlations with the PTSD Symptom Scale (PSS), hypertension diagnosis, and high body mass index (BMI). In receiver-operating characteristic (ROC) curve analysis, all IES-R models perfectly predicted the PSS (all area under the curve (AUC) >0.9, p values <0.001). The IES-R, both hyperarousal subscales, and the IES-R3 intrusion subscale significantly predicted high BMI. Both avoidance subscales and the IES-R3 intrusion subscale, not the IES-R, significantly predicted hypertension. In conclusion, both IES-R structures can reliably measure PTSD symptoms. The IES-R, hyperarousal, and intrusion may be credible criterion variables for predicting high BMI within PTSD while the intrusion and avoidance subscales may reflect the cardiovascular consequences associated with PTSD more reliably than the IES-R itself. The IES-R subscales may predict cardiometabolic adversities in PTSD, signifying a need for proper assessment of lifestyle and the application of dietary and exercise interventions in order to lower physical morbidity in PTSD. Replicating the study in larger samples, which comprise different physical and mental conditions from heterogenous cultural contexts is pivotal to validate the results (e.g., in specific groups such as those with confirmed traumatic exposure and comorbid mood dysfunction).

Different prognostic scores have been applied to identify patients with non-small cell lung cancer who have a higher probability of poor outcome. In this study we evaluated whether Naples Prognostic Score, a novel index which considers both inflammatory and nutritional values, was associated with long-term survival. The study is a retrospective propensity score matching analysis of patients who underwent curative surgery for non-small cell lung cancer from January 2016 to December 2021. The score considered four pre-operative parameters: neutrophil to lymphocyte ratio, lymphocyte to monocyte ratio, serum albumin and total cholesterol. Kaplan-Meier method and Cox regression analysis were performed to evaluate the relation between the score and disease-free survival, overall survival and cancer-related survival. A total of 260 patients were selected for the study, reduced to 154 after propensity score matching. Post-propensity Kaplan-Meier analysis showed a significant correlation between Naples Prognostic Score and overall survival (p=0.018) and cancer-related survival (p=0.007). Multivariate Cox regression analysis further validated the score as an independent prognostic indicator for both these survivals (p=0.007 and p=0.010 respectively). Naples Prognostic Score proved to be an easily achievable prognostic factor of long-term survival in patients with non-small cell lung cancer after surgical treatment.

To evaluate the effect of middle meningeal artery embolization (MMAE) on chronic subdural hematoma (CSDH). We enrolled consecutive patients with CSDH who underwent burr hole craniostomy (BHC) between January 2021 and February 2023. The primary outcome was recurrence rate, defined as an increase of hematoma width on imaging compared with the immediate postoperative imaging at a 3-month follow-up. Secondary outcomes included the rate of complications and adverse prognosis. Cohorts were balanced using 1:2 propensity score matching (PSM). A total of 271 patients were eligible for this study and divided into the MMAE group (n=23) and the BHC group (n=205). Compared with the BHC group, there was more use of anticoagulant or antiplatelet medication (47.8% vs 22.4%, P=0.008), bilateral hematoma (19.5% vs 19.5%, P=0.043) and hematoma with septations (47.8% vs 21.5%, P=0.005) in the MMAE group. After PSM, 64 cases were finally successfully matched. The logistic analysis result showed that MMAE was associated with the decreased recurrence rate of CSDH in the cohort after PSM (OR 0.072, 95%CI 0.322~0.746, P=0.028) but not with the improved clinical prognosis (OR 0.065, 95%CI 0.533~4.786, P=0.562). MAAE has a positive therapeutic effect on reducing the recurrence rate of CSDHs as an adjunct postoperative treatment after burr hole surgery.

Background: Malnutrition was associated with worse survival outcomes, impaired quality of life, and deteriorated performance status across various cancer types. We aimed to identify risk factors for malnutrition in patients with epithelial ovarian(EOC) and impact on survival. Methods: In our prospective study, we included the patients with primary and recurrent EOC, tubal or peritoneal cancer conducted. We assessed serum laboratory parameters, body mass index, nutritional risk index, nutritional risk screening score(NRS-2002), and bio-electrical impedance analysis. Results: We recruited a total of 152. Patients >65 years-old, with ascites of >500 ml, or with platinum-resistant EOC showed statistically significant increased risk of malnutrition when evaluated by NRS-2002(p-values = 0.014, 0.001, and 0.007, respectively). An NRS-2002<3 was an independent predictive factor for complete tumor resectability (p=0.009). The patients with NRS-2002≥3 had a median overall survival(OS) of seven months (95% CI=0-24 months), as compared to the patients with NRS-2002<3 where median OS was 46 months(p=0,001). Phase angle(PhAα)≤ 4.5 was the strongest predictor of OS. Conclusion: Malnutrition is an independent predictor of incomplete cytoreduction in study population. It is an independent prognostic factor for poor OS. Preoperative nutritional assessment is an effective tool in identification of high-risk groups within EOC characterized by poor clinical outcome.

We propose a new theory beyond the standard model of elementary-particle physics. Employing the concept of a quantized spacetime, our theory demonstrates that the zero-point energy of the vacuum alone is sufficient to create all the fields, including gravity, the static electromagnetic field, and the weak and strong interactions. No serious undetermined parameters are assumed. Furthermore, the relations between the forces at the quantum-mechanics level is made clear. Using these relations, we quantize Einstein’s gravitational equation: Beginning with the zero-point energy of the vacuum, and after quantizing Newtonian gravity equation, we combine the energies of a static electromagnetic field and gravity in a quantum spacetime. Applying these results to the Einstein gravity equation, we substitute the energy density derived from the zero-point energy in addition to redefining differentials in a quantized spacetime. This is how we derive the quantized Einstein gravitational equation without assuming the existence of macroscopic masses. For the weak interaction, by considering plane-wave electron and the zero-point energy, we obtain a wavefunction that represents a β collapse. In this process, from a different point of view than Weinberg-Salam theory, we derive the masses of the W and Z bosons and the neutrino, and we calculate the radius and lifetime of the neutron. For the strong interaction, we previously reported an analytical theory for calculating the mass of a proton by providing a specific linear attractive potential obtained from the zero-point energy, which agrees well with the measurements. In the present study, we further calculate the strong interaction between two nucleons, i.e., the mass of the pi-meson. The resulting calculated quantities agree with the measurements, which verifies our proposed theory.

Textile and clothing is one of the most important industrial sectors, not only due to the significant number of jobs generated, but also because it addresses one of the people’s fundamental needs (clothing). It is, however, a sector with a huge environmental impact, all over the world, and also an important social impact, especially in developing countries. Sustainability in the Textile &amp; Clothing value chain is a known issue, concerning both environmental, and economical-social facets of sustainability. One way to improve sustainability in this sector is by measuring the environmental, economic and social impacts of value chain activities and, ultimately, computing an Environmental and Circular score for each batch of textile and clothing product, and an Economical and Social score for each involved firm, reflected in their products. The consumer will then have the opportunity and responsibility for selecting products with the least negative environmental, economical and social impact. This article presents the results of STVgoDigital project - PPS1, developed in Portugal with the aim of implementing the traceability of textile and clothing products, boosting sustainability in this sector, and preparing the ground for the implementation of the circular economy. More exactly, a blockchain-based textile and clothing value-chain traceability platform is presented, for tracing textile product lots and activities, along the value chain, classifying them with a score, which measures their environmental and social impact. The environmental, economic and social impact scores are based on a set of proposed indicators. The results are assessed through the presentation of a case study of a face towel (home textile) and a case study of a T-shirt (clothing).

Published in July 2018, TAILORx aimed to establish non-inferiority of endocrine therapy (ET) compared to addition of chemotherapy (CHT-ET) in hormone receptor positive, human epidermal receptor 2 negative (HR+/HER2-) breast cancer (BC) patients with a 21-gene intermediate (11-25) recurrence score (RS). While this hypothesis proved correct, the study did show benefit of addition of chemotherapy (CHT) in a subgroup of women under 50 years of age, and particularly in the RS 16-25. The aim of this present study was to look at how TAILORx findings, including changes in RS categories, impacted CHT implementation at one oncologic center in Basel, Switzerland, and to identify main factors leading to these changes. Methods: We conducted a retrospective study on HR+/HER2-, BC patients who underwent 21-gene genomic testing between 2010-2021, at our center. Patients with metastatic disease were not included. We identified 326 eligible patients, of which 165 had a BC diagnosis before TAILORx (cohort A) and 161 after TAILORx publication (cohort B). Results: Demographic and tumor characteristics were similar in the two cohorts, although cohort B included significantly more women under the age of 50 when compared to A (34% vs. 24%, p<0.001). Median age and mean RS results were comparable 59 (IQR 16) in A and 58 (IQR 19) years in B and 17.72 (SD9.59) in A and 17.89 (SD9.53) in B, respectively. Patients in cohort A were slightly more overweight when compared to B (55% vs. 40% respectively, p<0.001). Most patients had stage II tumors of NST histologic type. Tumors in cohort B had higher Ki-67 than cohort A (39% vs. 32%, p=0.010). When compared based on manufacturer’s and based on TAILORx thresholds there were no significant differences in RS distribution. However, changes in score category led to shifts in patient population distribution, leading to a 40% drop in the low RS (from 60% to 20%), a doubling in the intermediate RS (from 30% to 60%) and an increase of 5% in the high RS (from 8-10% to 15%). Most patients had conservative surgery, adjuvant radiotherapy (RT) and ET. Overall CHT recommendation and application did not differ significantly in B vs. A. There was a reduction of 1% in the intermediate RS (11-25) and an increase of 13% CHT-ET application in the high RS (>26) category. In cohort B we noticed an increase in CHT-ET application among women <50 years old (by 12.5%), in lobular carcinomas (by 10%), grade 3 tumors (by 2%), node positive BC (by 3%) and node negative (by 2%). Tumor board recommendation for CHT dropped by 1% in the post TAILORx era, with a notable reduction of 5% in the intermediate RS (11-25) category. However, overall CHT administration rate was 19% in cohort A and 22% in B (p=0.763). Tumor Board recommended CHT for 90% of the BC patients that would have otherwise been assigned to CHT according to new RS guidelines in A and for 85% in B, showing a trend for undertreatment. Logistic regression analysis showed significance of age in both cohort A (OR 1.05, 95% CI 1.01-1.11, p=0.03) and cohort B (OR 0.89, 95% CI 0.84-0.94), p<0.001), and of nodal status in both cohort A (=R 3.32 95% CI 1.09-10-06, p=0.034) and cohort B (OR 3.31, 95% CI 1.29-8.53, p=0.013), while intermediate and high RS seem to be more relevant in cohort A (OR 0.12, 95% CI 0.03-0.43, p=0.01 and OR 0.04, 95% CI 0.01-0.21, p<0.01). Overall logistic regression analysis showed relevance of age (OR 0.93, 95% CI 0.08-0.97, p=0.001), pN (OR 4.77, 95% CI 2.03-11.22, p<0.001) and RS categories (RS 11-25: OR 0.02, 95% CI 0.01-0.07, p<0.001; RS>26: OR 617.93, 95% CI 57.97-6587.16, p<0.001). Conclusion: Our findings are similar to those reported across several studies: while tumor board recommendation for CHT decreases in the intermediate RS category, there is an increase being reported in the high RS category, leading to overall minor changes in CHT application. Administration of CHT-ET seems to be increasing among younger women, with unfavorable histo-pathological factors, such as lobular carcinoma and G3 histologic grade. Before TAILORx there is a tendency for undertreatment (-10%), especially among older BC patients, which seems to be maintained and even deepened (-15%) in the post TAILORx era, pointing to a personalized decision-making approach among Swiss oncologists.

Data mining techniques have garnered significant attention within the realm of education. However, the procurement of ample student data poses a formidable challenge. In response to this challenge, we present a student dataset characterized by its size and distinctive attributes. This dataset encompasses various task-related topics interconnected through a learning pathway, thereby enabling researchers to delve into the data from novel perspectives. Moreover, it encompasses extensive longitudinal student behavioral data, a rarity that adds substantial value. Spanning the years from 2010 to 2021, our dataset comprises a cohort of 7,933 students, 64,344 test scores, and 183,390 behavior records, solidifying its status as a valuable resource for educational research. In our experiments, we achieved successful predictions of students' test outcomes based on behavioral learning data. The strengths of our dataset render it apt for analyzing the nexus between student conduct and academic performance, crafting personalized learning recommendations, and pursuing various other research pursuits.

(1) Background: Although multiple studies have reported on the therapeutic effects of Atezo+Bev for the treatment of NASH-related liver cancer, few studies have focused on its effect on liver reserve. Here, we aimed to compare the changes in hepatic reserve during the Atezo+Bev treatment of NAFLD/NASH-related HCC and of non-NAFLD/non-NASH-related HCC. (2) Methods: We retrospectively compared the changes in ALBI score in 109 patients with NAFLD/NASH or non-NAFLD/non-NASH during 12 weeks of treatment with Atezo+Bev for advanced HCC between September 2019 and January 2022. PSM was performed, and the OS, PFS, and PPS of the two groups were compared. (3)Results: The ALBI after 12 weeks of Atezo+Bev treatment was significantly worse in the NAFLD/NASH group than in the non-NAFLD/non-NASH group. Analysis of the 24 propensity score-matched pairs of cases with NAFLD/NASH or non-NAFLD non-NASH yielded similar results. The prognoses of the two groups were similar with respect to OS and PFS, but the NAFLD/NASH group had a significantly shorter PPS. The 24 matched pairs had similar OS and PFS, but the PPS of the NAFLD/NASH group was shorter. (4)Conclusion: Atezo+Bev treatment may worsen hepatic reserve, and there-fore life expectancy, in patients with NAFLD/NASH-related liver cancer.

Background: Neonatal transportation of sick newborns is a major predictor of outcome. Prompt identification of the sickest newborns allows immediate corrective intervention and outcome optimization. Multiple severity scores were developed, however an optimal score has not yet been identified. Aim: To identify a rapid, accurate, and easy to perform score predictive for neonatal mortality in outborn neonates. Material and methods: All neonates, irrespective of gestational age, admitted by transfer in our level III regional neonatal unit between 01.01.2015 and 31.12.2021 were included. Infants with congenital critical abnormalities were excluded. Sick neonatal score (SNS) was calculated and compared between survivors and non-survivors. Gestational age (GA), birth weight (BW), gender, Apgar score, place of birth, time between delivery and admission (AT), early onset sepsis were collected from medical records and compared between study groups. Subgroup analysis was performed based on gestational age (preterm versus term infants). A new score was elaborated, including GA, BW, and AT, namely MSNS-AT score, to further improve mortality prediction. The main outcomes were mortality prediction using SNS and MSNS-AT score. Univariable and multivariable analysis, including Cox regression, were performed using SPSS Statistic 22.0. P-value was considered statistically significant if <0.05, 95% confidence intervals, odds ratio and hazard ratios were calculated were appropriate. Results: A total of 418 outborn infants were admitted during study period; 15 infants were excluded due to critical congenital defects. Out of 403 outborn infants, 217 born prematurely (53.8%), 224 males (55.6%), 20 died (4.96%). Compared to the survivors, the non-survivor neonates had significantly lower GA, BW, and SNS score (p<0.05), although only SNS score remained significantly lower in all subgroups (preterm vs term infants). A SNS score ≤8 was associated with mortality both in the whole study group and in subgroups (p<0.001). Time to admission was significantly associated with increased mortality rate in the whole group (p<0.05) and in preterm infants but not in term ones (p>0.05). In univariable and multivariable Cox regression models, MSNS-AT score, with a cut-off optimal value of ≤10 was more precise in predicting mortality compared to SNS (AUC 0.735 vs. 0.775) when applied to the entire group, had a lower accuracy in the term infants (AUC 0.765 vs 0.809) and a better accuracy the preterm infants group (AUC 0.885 vs. 0.810). Conclusions: The MSNS-AT score – calculated by adding GA, BW, and AT to the SNS score - significantly improved mortality prediction at admission in the whole study group as compared to SNS score. The best accuracy prediction of MSNS-AT score was observed in preterm infants suggesting that, besides GA and BW, TA may be decisive for the outcome of outborn preterm infants. Further studies are necessary to confirm the predictive value of MSNS-AT score and to identify variables that can improve its value in term infants without affecting the simplicity, ease, and rapidity of the scoring system.

1. Background: Cardiovascular diseases (CVDs) are India’s leading cause of mortality. This study aimed to recalibrate the original Framingham Risk Score (FRS) equations among adults in Kerala state. 2. Methods: Baseline survey data from the Kerala Diabetes Prevention Program were analyzed: 921 males and 567 females for lipid-based FRS scores and 1042 males and 646 females for BMI-based FRS scores. Recalibration of the original FRS scores was performed using local data on CVD risk factors and CVD mortality. 3. Results: Among males, the median 10-year CVD risk with the recalibrated lipid-based FRS score was 7.34 (IQR 4.33-12.42), compared with the original score of 8.88 (5.23-14.87) (p<0.001). For BMI-based FRS scores, the median 10-year CVD risk was 7.40 (4.27-11.83) with the recalibrated score, compared to 9.32 (5.40-14.80) for the original score (p<0.001). In females, the median 10-year CVD risk was 4.83 (2.90-8.36) with the recalibrated score, compared to 2.85 (IQR 1.71-4.98) with the original score (p<0.001). Similarly, the median 10-year CVD risk was 4.66 (2.74-8.81) with the recalibrated BMI-based FRS score, compared to 2.95 (1.72-5.61) with the original score (p<0.001). 4. Conclusions: Recalibrated FRS scores estimated a significantly lower 10-year CVD risk in males and a higher risk in females than the original FRS scores.

The duality is one of the most interesting properties of the Laplace and Fourier transforms associated to the integer order derivative. Here, we will generalize it for fractional derivatives and extend the results to the Mellin, Z and discrete-time Fourier transforms. The scale and nabla derivatives are used.

We report on recent experimental results on β decay into self-conjugate (N=Z) nuclei with mass number 58≤A≤70. Super-allowed β decays from the Jπ=0+ ground state of a Z=N+2 parent nucleus are to the isobaric analogue state, through so-called Fermi transitions, and to Jπ=1+ states, by way of Gamow–Teller (GT) transitions. The operator of the latter decay is a generator of Wigner’s SU(4) algebra and as a consequence GT transitions obey selection rules associated with this symmetry. Since SU(4) is progressively broken with increasing A, mainly as a consequence of the spin–orbit interaction, this symmetry is not relevant for the nuclei considered here. We argue, however, that the pseudo-spin–orbit splitting can be small in nuclei with 58≤A≤70, in which case nuclear states exhibit an approximate pseudo-SU(4) symmetry. To test this conjecture, GT decay strength is calculated with use of a schematic Hamiltonian with pseudo-SU(4) symmetry. Some generic features of the GT β decay due to pseudo-SU(4) symmetry are pointed out. The experimentally observed GT strength indicates a restoration of pseudo-SU(4) symmetry for A=70.

This paper proposes a non-extensive entropy econometric technique to predict energy efficiency at province (NUT-2) level based on imperfect knowledge of the national overall efficiency in the sectors of industry, transport, households and services. The model is applied to the polish case. As acknowledged in recent literature, non-extensive entropy model should remain a valuable device for econometric modelling even in the case of low frequency series since outputs provided by the Gibbs-Shannon entropy approach correspond to the Tsallis entropy limiting case of the Gaussian law when the Tsallis q-parameter converges to unity. Therefore, we set up a q-Tsallis-Kullback-Leibler entropy criterion function with a priori consistency moment and model data constraints, including province energy intensity (known with uncertainty), regional climate differentiation and regular conditions. The model outputs continue to conform to empirical expectations. In spite of the close to unity q-Tsallis parameter, this Tsallis related approach reflects higher stability for parameter computation in comparison with the Shannon-Gibbs entropy econometrics technique. The proposed technique can be applied in different EU countries and elsewhere for example in the context of experimental official statistics.

In medico-administrative database, certain prognostic factors cannot be taken into account. The main objective was to estimate the performance of two models based on two databases: Epi-thor clinical and medico-administrative databases. For each of the two databases, we randomly sampled a development dataset with 70% of the data and a validation dataset with 30%. Performance of models was assessed by Brier score, the area under the receiver operating characteristic (AUC ROC) curve and the calibration of the model. For Epithor and medico-administrative databases, the development dataset included 10,516 patients (with resp. 227 (2.16%) and 283(2.7%) deaths) and the validation dataset included 4,507 patients (with resp. 93 (2%) and 119 (2.64%) deaths). 15 predictors were selected in the models (including FEV, Body Mass Index, ASA score and TNM stage for Epithor). The Brier score values were similar in the models of the two databases. For validation data, the AUC ROC curve was 0.73 [0.68-0.78] for Epithor and 0.8 [0.76-0.84] for medico-administrative databases. The slope of the calibration plot was less than 1 for the two databases. This work shows the good performances of a model developed from a medico-administrative database, despite the absence of clinical variables used in practice by surgeons, such as FEV1, ASA score or TNM stage.

The scalp is a unique anatomical region with distinct challenges for reconstruction, especially in cases of melanoma excision. This study explores the utilization of the O-Z flap technique as an alternative approach for patients with melanoma, where traditional free flap reconstruction may not be feasible due to age or underlying health conditions. However, in this case, the patient had a history of angina and was unwilling to undergo a long operation due to his advanced age. This study highlights the importance of following NCCN guidelines for melanoma resection margins based on tumor thickness and underscores the value of staged resection planning to minimize deficits. This requires an individualized approach as each patient may have different circumstances (general health condition, age, compliance, etc.). So we planned a staged excision first. In the first surgery, we would resect the tumor minimally and then determine the exact size of the tumor. Then, in the second surgery, we resected it with a safety margin according to the guidelines. The O-Z flap, a local flap with an "O"-shaped defect and "Z"-shaped incision line, is introduced as a reconstructive option. The surgical procedure, advantages, and limitations of this approach are discussed. This study provides valuable insights into achieving successful scalp reconstruction while considering aesthetic outcomes and patient-specific factors.

The development of photocatalysts with a wide spectral response and effective carrier separation capability is essential for the green degradation of tetracycline. In this work, a magnetic recyclable Z-scheme ZnO/ZnFe2O4 heterojunction (ZZF) was successfully constructed by the solid phase method using MIL-88A(Fe)@Zn as the precursor. Appropriate band gap width and Z-scheme charge transfer mechanism make ZZF have excellent visible light absorption performance, efficient charge separation and strong redox ability. Under visible light irradiation, the degradation efficiency of TCH for optimal sample ZZF2 can reach 86.3 % within 75 min in deionized water, and achieve 92.9 % within 60 min in tap water, which exhibits superior stability and reusability after five cycles. Moreover, the catalyst in the water can be conveniently recovered by magnetic force. After visible light irradiation for 70 minutes, the temperature of the reaction system increased by 21.9 °C. Its degradation constant (35.53×10-3 min-1) increases 5.1 times that at room temperature (6.95×10-3 min-1). Thermal energy perfects the kinetic driving force of the reactants and promotes carrier migration to produce more •O2- and •OH. This work provides a potential candidate and inspires the design of photocatalyst for tetracycline hydrochloride degradation.

Based on survey data from 297 beef cattle farmers in five provinces, Hunan, Ningxia, Inner Mongolia, Shandong and Gansu, the impact of the package of support policies on farmers' beef cattle production was assessed by means of propensity score matching (PSM). The results showed that the package of support policies, the education level of the household head, participation in beef cattle professional cooperatives and taking out loans for beef cattle farming had significant positive impacts on farmers’ inventories of beef cattle and breeding cows. The current package of beef cattle support policies implemented by the national and local governments has significantly promoted the production of beef cattle by farmers, and the effects of the policy implementation have been positive. The implementation of the relevant support policies led to increases in farmers’ inventories of approximately 17 head of beef cattle and approximately 9 head of breeding cows. The contribution rates of the policy implementation to the beef cattle and breeding cow inventories reached 52.96% and 67.30%, respectively.

In this paper, we present demographic, clinical, anamnestic, cognitive, and functional data, as well as haematological, haematochemical, immunological and genetic parameters of an exceptional individual: Antonino Turturici, a semi-supercentenarian who held the title of the oldest living Italian centenarian from December 28, 2020, to September 23, 2021. The purpose of this study is to offer fresh insights into extreme phenotypes, with a particular focus on immune-inflammatory parameters. To the best of our knowledge, this study represents the first phenotypic investigation of a semi-supercentenarian, illustrating both indicators of age-related immune phenotype (ARIP) recognized as significant gauges of biological ageing and INFLA-score, a metric designed to assess the cumulative impact of inflammatory markers. The aim of this study was, indeed, to advance our understanding of the role of immune-inflammatory responses in achieving extreme longevity. The results bolster the idea that the immune system can play a role in promoting extreme longevity. However, this does not exclude the involvement of other body systems or organs in achieving extreme longevity.

Building heterojunction is promising strategy for the achievement of highly efficient photocatalysis. In this study, a novel SnIn4S8@ZnO Z-scheme heterojunction with tight contact interface was successfully constructed through a facile two-step hydrothermal method. The phase composition, morphology, and photophysical properties of SnIn4S8@ZnO were studied through a series of characterization methods, respectively. Methylene blue (MB) was selected as the target pollutant for photocatalytic degradation and the degradation process was fitted with pseudo-first order kinetics. The as-prepared SnIn4S8@ZnO heterojunctions exhibited outstanding photocatalytic activities for the degradation of MB. The optimized sample (ZS800), in which the molar ratio of ZnO to SnIn4S8 was 800, displayed the highest photodegradation efficiency of MB (91%) within 20 min. Furthermore, the apparent rate constant of photodegradation for MB of ZS800 (0.121 min−1) was 2.2 times higher than that of pure ZnO (0.054 min−1). The improvement of photocatalytic activity could be attributed to the effective spatial separation of photogenerated charge carriers through a Z-scheme heterojunction with intimate contact interface. This work will provide a new insight into constructing excellent ZnO-based photocatalytic systems for wastewater purification.

As a rapidly expanding family of two-dimensional (2D) materials, MXenes have recently gained considerable attention due to their appealing properties. Here, by developing a solution-based coating method that enables transfer-free and layer-by-layer film coating, we investigate the layer-dependent nonlinear optical absorption of Ti₃C₂T_x films ‒ an important member of the MXene family. By using the Z-scan technique, we characterize the nonlinear absorption of the prepared MXene films consisting of different numbers of monolayers. The results show that there is a strong and layer-dependent nonlinear absorption behavior, transitioning from revisable saturable absorption (RSA) to saturable absorption (SA) as the layer number increases from 5 to 30. Notably, the nonlinear absorption coefficient β varies significantly within this range, changing from ~7.13 × 10² cm/GW to ~-2.69 × 10² cm/GW. We also characterize the power-dependent nonlinear absorption of the MXene films at various incident laser intensities, and a decreasing trend in β is observed for increasing laser intensity. These results reveal the intriguing layer-dependent nonlinear optical properties of 2D MXene films, highlighting their versatility and potential for implementing high-performance nonlinear photonic devices.

An empirical investigation was carried out to study the relationship between the soil characteristics, including the Nitrogen (N), Phosphorus (P), Potassium (K), potential of Hydrogen (pH), Electrical conductivity (EC), Sulfur (S,), Zinc (Zn), Iron (Fe), Copper (Cu), Manganese (Mn) and Boron (B) using principal component analysis (PCA), Factor Analysis (FA), and Canonical Correlation analysis (CCA) for data reduction multivariate techniques. The first five main components accounted for 24.22%, 18.52%, 16.1%, 9.97%, and 9.27% of sample variances, respectively. All five principal components (PCs) accounted for 78.07% of the sample variance. The soil characteristics viz., P and K have highly dominated the first PC; the soil characteristics N and pH have dominated the second PC; K, EC, and Cu have dominated the third PC; Fe, Mn, and pH have dominated in the fourth PC; whereas the parameter Cu dominated the fifth PC. The first factor showed a strong negative loading on S and a strong favorable loading on Cu; P, K, and EC have substantial positive loadings in the second factor. Significant positive loadings on Mn, Fe, Cu, pH, N, and K are present in the third component. The fourth factor had a significantly positive pH, Fe, N, P, K, and B loadings. Fe, P, and B have much weight in the fifth factor. The soil characteristics viz., N, Zn, pH, K, Fe, and Mn have dominated the first PC; the soil characteristics B, P, S, Zn, and Fe have dominated the second PC; B and P have dominated the third PC whereas the only character Cu dominated the fourth PC. Cu and OC have much weight in the fourth factor. The canonical redundancies for dependent and independent sets are 12% and 17%, respectively. The Stewart-Love canonical redundancy index is 70.58%, which means that the first linear combination of the X-set explains 70.58% of the total variance in the Y-set.

This study aimed to investigate the atherogenicity (quality) of LDL particles in patients with acute and recovered from COVID-19 infection. The participants were adults, aged 18 years or older of both sexes. Those with positive RT-PCR results at baseline were included in the Acute COVID-19 group (n=33), and those with negative RT-PCR six months after acute infection, were included in the Recovered COVID-19 group (n=30). The LDL quality was evaluated using three validated methods: Z-scan, UV-visible spectroscopy, and Lipoprint. The Recovered COVID-19 group showed significantly higher numbers of large LDL particles (less atherogenic) than the Acute COVID-19 group (P&lt;0.05). We also found that COVID-19 infection was associated with the oxidative modification of LDL particles. D-dimer and CRP levels were correlated with Z-scan results and antioxidant-amount estimate. Moreover, we noticed that the infection left a sequel in LDL quality, even after six months of recovery. These findings highlight the importance of monitoring lipids during and after recovery from COVID-19 infection, and their potential deleterious effect on the LDL profile might correlate with the progression of atherosclerosis and poor clinical outcomes.

contaminated sites located in each school district. Previous studies showed that various environmental factors, such as exposure to toxic substances negatively impacts human health depending on their concentration and occurrence. Therefore, the study aims to use Geographical Information System (GIS) technology and secondary data on IEP numbers of each school district, chemical occurrence in contaminated sites, and demographic data to conduct a correlational analysis. The secondary data obtained from school districts and contaminated sites from Iowa Department of Natural Resources Facility Explorer were populated in ArcMap 10.5 (a GIS software) for generating maps and data to conduct statistical analysis. The contaminants were categorized into metals, polyaromatic hydrocarbons (PAH), and solvents with weighing factors as 1, 0.5, and 0.25. A total of 1 Superfund site and 39 CERCLA sites were identified as contaminated sites for this study. The majority of contaminants were heavy metals such as lead, arsenic, mercury, and cadmium. The mean toxic score of all contaminated sites combined was 13.4 (sd 14.4). The correlational analysis between the IEP numbers from each school districts and toxic scores from the contaminated sites was positive indicting that increased toxic score increased the number of students enrolled in the IEP program (F=23.7, p<0.0001). The correlational analysis between toxic score and demographics indicated some interesting results. Children under the age of 10 were living in areas with high toxic score and the showed mild correlation (p<0.00052). Similarly, higher number of black population resided in areas with high toxic score (p=0.0032) than the white population (p<0.0001). The result also indicated that children enrolled in IEP were predominantly among the black population (p<0.0001). The correlational analysis between household income and poverty percentage of people residing near the contaminated area indicated that people had low average household income (p=0.0002) and high poverty percentage (p=0.0203) residing in areas with higher toxic score. Regarding the educational status, less number of people with post graduate degree (p<0.0001) resided in areas with high toxic score and more number of people with no degree (p<0.0001) resided in areas with high toxic score. Finally, the study showed the increasing trend of eligible children enrolling in free and reduced lunch programs with increasing toxic scores (p=0.0012) and IEP levels (p=0.0416). This study emphasize on developing multiple exposure to correlate environmental factors contributing to the negative health outcome on people.

Z-ligustilide is a main active ingredient in the volatile oil of Angelica sinensis, a traditional Chinese medicine. Cisplatin is a commonly used chemotherapy drug for the treatment of lung cancer. Efficacy is often limited by the development of drug resistance after long-term treatment. Here, we investigated the effect of the combination of Z-ligustilide and cisplatin (Z-ligustilide+cisplatin) on resistance of cisplatin-resistant lung cancer cells and its action mechanism. Cell viability was analyzed by cell counting kit-8 (CCK-8) assay. Cell cycle and cell apoptosis were examined by flow cytometry assay. mRNA and protein levels of factors related to cell cycle and apoptosis were analyzed by real-time PCR and western blot. Liquid chromatography-mass spectrometry (LC-MS) analysis and RNA sequencing in A549, A549/DDP and A549/DDP cells treated with the Z-ligustilide+cisplatin were performed. The expression of PLPP1 was analyzed by the Cancer Genome Atlas (TCGA). The correlation between PLPP1 and prognosis was evaluated by immunohistochemistry and Kaplan-Meier (KM) plotter analysis. We found that Z-ligustilide+cisplatin could decrease the cell viability of cisplatin-resistant lung cancer cells. Z-ligustilide+cisplatin induced cell cycle arrest, and promoted cell apoptosis of cisplatin-resistant lung cancer cells. Metabolomics combined with transcriptomics revealed that Z-ligustilide+cisplatin inhibited phospholipid synthesis by upregulating the expression of PLPP1. Furthermore, PLPP1 expression was positively correlated with good prognosis. Knockdown of PLPP1 abolished the effects of Z-ligustilide+cisplatin on cell cycle and apoptosis. Z-ligustilide+cisplatin inhibited the activation of AKT by reducing the levels of PIP3 levels. Z-ligustilide+cisplatin induced cell cycle arrest and promoted cell apoptosis of cisplatin-resistant lung cancer cells by inhibiting PLPP1-mediated phospholipid synthesis.

As various services have been generating large scale graphs to represent multiple relationships between objects, studies have been conducted to obtain subgraphs with particular patterns. In this paper, we propose a distributed query processing method to efficiently search a subgraph for a large graph on Spark. To reduce unnecessary processing costs, the search order is determined by filtering scores using the probability distribution. The partitioned queries are searched in parallel in the distributed graph of each slave node according to the search order, and the local search results obtained from each slave node are combined and returned. The query is partitioned in triplets based on the determined search order. The performance of the proposed method is compared with the performance of existing methods to demonstrate its superiority.

Gastric cancer is among the top 5 causes of cancer-related death worldwide. Preoperative chemotherapy has been established as an option in patients with locally advanced gastric cancer. However, chemotherapy yields variable results, owing to the cellular and molecular heterogeneity of this disease. Identifying patients who did or did not respond to preoperative therapy can allow clinicians to alter treatment modalities and provide important information related to prognostication. Pathologic response to preoperative therapies, called Tumor Response Grade (TRG), has been evaluated to quantify treatment response. Multiple systems for TRG have been established. However, literature has demonstrated inconsistent results for TGR systems and prognosis, possibly due to variability in interpretation of tumor response between systems and interobserver variability. Radiographic response to preoperative therapies using RECIST 1.1 criteria and endoscopically-assessed tumor response have demonstrated association with survival; however their use in gastric cancer remains challenging given the inability to accurately and consistently identify and measure the tumor, especially in the setting of neoadjuvant therapy where treatment-related changes can obscure the gastric wall layers. This review is focused on summarizing the available literature related to evaluating TRG in gastric cancer, as well as providing a brief overview on the use of radiographic and endoscopic methods to assess response to preoperative therapies. Lastly, we outline future directions regarding the use of a universal TRG system to guide care and assist with prognosis.

Early diagnosis and appropriate treatments are crucial to reducing mortality risk in septic patients. Low SOFA scores and current biomarkers may not discern adequately patients that could develop severe organ dysfunction or have an elevated mortality risk. The aim of this prospective observational study is to evaluate the predictive value of the biomarkers midregional proadrenomedullin (MR-proADM), procalcitonin (PCT), C-Reactive Protein (CRP), and lactate for 28-day mortality in patients with sepsis and a SOFA score ≤ 6. 284 patients were included, with a 28-day all-cause mortality of 8.45 % (N=24). Non-survivors were older (p=0.003), required mechanical ventilation (p=0.04) and were ventilated for longer (p=0.02), had a higher APACHE II (p=0.015) and SOFA (p=0.027) scores. Lactate showed the highest predictive ability for all-cause 28-day mortality with an area under the receiver-operating characteristic curve (AUROC) of 0.67 (0.55–0.79). The AUROC for all-cause 28-day mortality in patients with community-acquired infection was 0.69 (0.57–0.84) for SOFA, and 0.70 (0.58–0.82) for MR-proADM. A 2.1 nmol/L cut-off point for this biomarker in this subgroup of patients discerned with 100% sensibility survivors from non-survivors at 28 days. In patients with community acquired sepsis and initial SOFA score ≤ 6, MR-proADM could help identify patients at risk of 28-day mortality.

In the face of escalating cybercriminal sophistication, an innovative approach to network anomaly detection has been pursued in this longitudinal study, integrating computational data analytics in a geographic, organizational, and behavioral context. A data-driven scoring mechanism was employed to systematically analyze and correlate source countries of IP addresses and organization-associated Autonomous System (AS) Numbers (ASN) with network anomalies. Significant correlations between certain countries, specific organizations, and high behavior scores were identified through the data analytics. An increase in connection requests was also found to be linked with elevated behavior scores. Validated by cross-validation techniques, these findings emphasize the necessity for continuous model recalibration. The transformative role of integrative data analytics in cybersecurity is underscored, paving the way for the development of more sophisticated, context-aware anomaly detection systems. Specifically, the analysis underscores the need for organizations to adopt a proactive and adaptive approach to cybersecurity that can keep pace with the evolving threat landscape.

The increased emergence of multidrug-resistant Helicobacter pylori influences the prevention of stomach cancer. Zingiber officinale is a plant usually used in folk medicine to treat a variety of diseases involving infections, nausea, vomiting, peptic ulcer, dyspepsia, and inflammation. This study was conducted to evaluate the ability of Z. officinale extract to combat resistant H. pylori. The disc diffusion, microdilution, and microplate assays were performed to evaluate the susceptibility to antibiotics, and the antibacterial and antibiofilm activities of the Z. officinale extracts. Using the checkerboard method, the combined effects of the gentamicin and Z. officinale extract were investigated. In addition, anti-inflammatory activity and GC-MS analysis were determined by the modified protocol. According to the findings, H. pylori isolates exhibited resistance rates of 56.33, 50.0, and 45.85 for metronidazole, gentamicin, and tetracycline, respectively. The methanolic extract of Z. officinale had the strongest effectiveness against resistant H. pylori isolates with MIC of 20.0 to 50.0 µg/ml against both H. pylori isolates and the stranded strain NCTC 11637. Z. officinale extract suppress the biofilm formed by H. pylori isolates with a percentage of 92.96% at 50.0µg/ml, compared with 97.19% for gentamicin at the same concentration. According to FICI values, combination of methanolic Z. officinale extract to gentamicin increases bacterial sensitivity to such drugs. Moreover, the Z. officinale extract exhibits strong anti-inflammatory activity. The GC-MS analysis of Z. officinale extract exhibits 17 different chemical compounds. Conclusions: The Z. officinale extract contain the anti-inflammatory compound gingerol as the main constituent which inhibits the growth of H. pylori and its biofilm, are a promising natural therapeutic alternative or enhance antibiotics activity

Arsenic (As) contamination of groundwater is a common problem in BDP. The alkaline pH of the groundwater provides favourable condition for geomicrobiochemical processes, where organic matter also plays an important role in mobilization of As. The total arsenic content (AsT) of the groundwater is in the range of 69-178 µgL-1 with mean value of 118.58 µgL-1. The groundwater quality of monitored drinking water wells are related to local land–use pattern and rural sanitation installation and practices (which can have a strong influence on microbial contamination). The study indicates that As heterogeneity, probably a consequence of microbial heterogeneity is a feature of the study area. The excessive total and fecal coliform (TC and FC) count of the ponds possibly suggest uncontrolled surface run offs and sewage leakage, notably from nearby pit-latrine, which increased the microbial contamination in these water sources. The tube wells located in close proximity (~ 2-3 m) of the surveyed ponds are also contaminated with high TC and FC values, due to faulty water supply system, pond water infiltration and cracked tube well platforms. Coliforms may influence geomicrobiological processes in groundwater and thereby, contribute in As release and mobilization. The TC and FC values of monitored tube wells and ponds show seasonal variation, with high TC and FC values during wet season. Attempt has been made to focus on sanitation risk of the monitored wells (based on sanitation and fecal coliform scores) which is usually less explored. The sanitary risk score reveal the need of immediate attention to all the sites, as 25.0 %, 58.3 %, 11.1 % and 5 % of tube wells of the six sites fell under very high risk (sanitary risk score ≥ 9), high risk (sanitary risk score 6-8), intermediate risk (sanitary risk score 3-5) and low risk category (sanitary risk score 0-2), respectively. Fecal coliform score classified all the sites under intermediate risk category (FC count 10-100 per 100 ml of water). The predominance of As heterogeneity particularly in areas under high risk category (showing high TC and FC contamination) is observed along with the similar sinusoidal pattern of TC, FC and AsT content. Finally, this study shed light on the factors responsible for unsafe nature of monitored tube wells and the influence of anthropogenic activities on the microenvironment of the groundwater, which could be a probable reason behind the As heterogeneity in the groundwater of the study area.

Abstract: Based on the survey data of 5 large grain-producing provinces in China, this paper studies the effect of agricultural production trusteeship on agricultural carbon emission reduction by using a propensity score matching method. The empirical results show that the carbon emission of wheat reduces by 7.107kg/mu, with a decrease rate of 15.5% after participating in agricultural production trusteeship. Among them, chemical fertilizers, manpower input, agricultural chemicals and diesel oil respectively reduces with rates of 14.2%, 27.7%, 14.1%, and 6%. However, there are differences in the facilitation effects of different trusteeship services, with the best promotion effect of field management services, followed by cultivation, planting and harvest services, and then agricultural material supply services, the ATT is -6.160, -5.732 and -5.530, respectively. Meanwhile, there are differences in the promotion effects for farm households with different factor endowments. The promotion effect is better for small farm households with 1 type of agricultural machinery or less, and an operation scale of 7 mus or less. Therefore, in order to better play the role of agricultural production trusteeship on agricultural carbon emission reduction, the government should vigorously support its development and guide more smallholders to choose agricultural production trusteeship.

Diet modification may be a potential contributor in the prevention of age-related cognitive decline. The association between dairy product consumption and cognitive function remains unknown in older people. We investigated whether cheese intake is associated with lower cognitive function (LCF) in community-dwelling older adults. This cross-sectional study included 1503 adults aged over 65 years. Analyzed data were obtained from face-to-face interviews and functional ability measurement. Cognitive function was assessed using mini-mental state examination (MMSE), and a score ≤ 23 was defined as LCF. The prevalence of LCF was 4.6% and this group had smaller calf circumference, slower usual walking speed, and more frequent history of anemia than subjects with MMSE scores ≥ 24. After adjusting for confounding factors, logistic regression analysis revealed cheese intake (odds ratio (OR) = 0.404, 95% confidence interval (CI) = 0.198-0.824), age (OR = 1.170, 95% CI = 1.089-1.256), usual walking speed (OR = 0.171, 95% CI = 0.062-0.472) and calf circumference (OR = 0.823, 95% CI = 0.747-0.908) as significant factors associated with LCF. Although the present study was an analysis of cross-sectional data of Japanese community-dwelling older adults, the results suggest that cheese intake is inversely associated with LCF.

In econometrics and finance, volatility modelling has long been a specialised field for addressing a variety of issues pertaining to the risk and uncertainties of an asset. This study presents a robust framework, through a step-by-step design, that is relevant for effective Monte Carlo simulation (MCS) with empirical verifications to estimate volatility using the Generalized Autoregressive Score (GAS) model. The framework describes an organised approach to the MCS experiment that includes "background (optional), defining the aim, research questions, method of implementation, and summarised conclusion". The method of implementation is a workflow that consists of writing the code, setting the seed, setting the true parameter a priori, data generation process, and performance assessment through meta-statistics. Among the findings, it is experimentally demonstrated in the study that the GAS model with a lower unconditional shape parameter value can generate a dataset that adequately reflects the behaviour of financial time series data, relevant for volatility estimation. This dynamic framework is intended to help interested users on MCS experiments utilising the GAS model for reliable volatility calculations in finance and other areas.

Background and aim: To explore the discriminant accuracy of Cytokeratin 18 (CK18, including M65 and M30 forms) for an elevated fatty liver index (FLI) as a validated proxy of Non-Alcoholic Fatty Liver Disease (NAFLD), and cardiovascular disease (CVD) risk in the general population. Methods: Both serum CK18 forms were measured using a commercial immunoassay in randomly selected samples from 312 participants of the PREVEND general population cohort. FLI ≥60 was used to indicate NAFLD. Framingham Risk Score (FRS) and the SCORE2 were used to estimate the 10-year risk of CVD. Receiver Operating Characteristic (ROC) curve, linear/logistic regression models and Spearman's correlations were used. Results: Intricate associations were found between CK18, FLI and CVD risk scores. While M30 was the only independent predictor of FLI≥60, M65 discriminated best NAFLD individuals at very-high 10-years CVD risk according to SCORE2 (AUC:0.71; p=0.001). Values above the predefined manufacturer cut-off (400 U/l), were associated with an independent 5-fold increased risk (adjusted odds ratio: 5.44, p=0.01), with negative predictive value of 93%. Conclusions: Confirming that NAFLD is associated with an increased CVD risk, our results point to CK18 M65 as a candidate biomarker to identify NAFLD individuals at low CVD risk in European general population.

A retrospective cohort study was performed to determine the likelihood of malignant stroke after mechanical thrombectomy via ASPECTS-PASS score(A-P score), a novel scoring system using ASPECT score and number of arterial-passes. This prediction score is designed to help clinicians take early measures. Malignant stroke is defined as a large MCA infarct with mass effect that develops during the first 5 days following presentation and is associated with approximately 80% mortality. Previous studies have shown an association of low ASPECTS and high number of passes with poor outcome.We performed a retrospective cohort analysis on 78 patients with anterior circulation stroke who underwent mechanical thrombectomy at our hospital. We analyzed the likelihood of developing malignant stroke post thrombectomy in the first 5 days following successful recanalization (TICI ≽ 2b). Malignant stroke is defined as severe symptoms secondary to edema as evidenced by midline shift, cistern engorgement, and hemorrhagic conversion with edema. Patients with ASPECTS of 0-5 were excluded. We used two variables to predict the outcome: ASPECT score and number-of-passes. We used the equation ASPECT score minus number-of-passes (A-P) to arrive at a single number to predict the risk of malignant stroke. A-P scoring scale ranged from 0-9. Our study showed a statistically significant inverse relationship of A-P score and risk of malignant stroke. Approximately 90% of patients with A-P score < 5 developed malignant stroke in our study. A-P score can help predict malignant stroke post thrombectomy even after successful recanalization. Thus, A-P score of ≤ 5 suggests very high risk. (A-P) Score can assist clinicians to take early measures, and thereby prevent worse outcomes.

Oestrogen receptor expression in breast cancer (BC) cells is a marker of high cellular differentiation and allows the identification of two BC groups (ER-positive and ER-negative) that, although not completely homogeneous, differ in biological characteristics, clinical behaviour and therapeutic options. The study, based on three publicly available EWAS datasets, focuses on the comparison between these two groups of breast cancer using an epimutation score. The score is calculated not only based on the presence of the epimutation but also on the deviation amplitude of the methylation outlier value. For each dataset, we performed a functional analysis based first on the functional gene region of each annotated gene (we aggregated the data per gene region TSS1500, TSS200, first-exon, body-gene identified by the information from the Illumina Data Sheet) and then we performed a pathway enrichment analysis through the REACTOME database based on the genes with the highest epimutation score. Thus, we blended our results and found common pathways for all three data sets. We found that a higher and significant epimutation score due to hypermethylation in ER-positive BC is present in the promoter region of the genes belonging to the SUMOylation pathway, the NOTCH pathway, the IFN-$\gamma$ signalling pathway and the deubiquitination protease pathway; while a higher and significant level of epimutation due to hypomethylation in ER-positive BC is present in the promoter region of the genes belonging to the ESR-mediated pathway. The presence of this state of promoter hypomethylation in the ESR-mediated signalling genes is consistent and coherent with an active signalling pathway mediated by oestrogen function in the group of ER-positive BC. SUMOylation and NOTCH pathways are associated with BC pathogenesis and have been found to play distinct roles in the two BC subgroups. We speculated that the altered methylation profile may play a role in regulating signalling pathways with specific functions in the two subgroups of ER-BC.

This study addresses the motivations behind Generation Z's attendance at conferences and aims to contribute to a better understanding of their conference participation behavior. The study identified six latent factors that influence conference attendance motivation: Green and Digital Conference Experience, Educational and professional opportunities, Conference costs, Destination and conference stimuli, Stimulating factors, and Conference accessibility. These factors align with Generation Z's unique characteristics and preferences, such as their environmental consciousness, reliance on digital technologies, desire for continuous learning, career advancement, and experiences. The study also found that destination characteristics and educational and professional opportunities are significant motivators for Generation Z's conference attendance across different cultural contexts. Additionally, Generation Z's strong interest in sustainability and financial challenges highlights the need for eco-friendly practices and affordable registration fees to make conferences more appealing and accessible. The study further explores the impact of socio-demographic characteristics, revealing the gender and past conference attendance differences in motivation. Finally, the study discusses the implications for the conference industry and suggests areas for future research to enhance the understanding of conference attendance motivation among Generation Z.

Blood cell analysis is a crucial diagnostic process in medical practice. In particular, detecting white blood cells (WBCs) is essential for diagnosing of many diseases. The manual screening of blood films is a time-consuming and subjective process, which can lead to inconsistencies and errors. Therefore, automated detection of blood cells can improve the accuracy and efficiency of the screening process. In this study, an explainable Vision Transformer (ViT) model was proposed for the automatic detection of WBCs from blood films. The proposed model utilizes the self-attention mechanism to extract relevant features from the input images and leverages transfer learning by incorporating pre-trained model weights to improve its performance. The proposed model achieved a classification accuracy of 99.40% for five distinct types of WBCs and exhibited potential in reducing the time required for manual screening of blood films by pathologists. Upon examination of the misclassified test samples, it was observed that incorrect predictions were correlated with the presence or absence of granules in the cell samples. To validate this observation, the dataset was divided into two classes, namely Granulocytes and Agranulocytes, and a secondary training process was conducted. The resulting ViT model trained for binary classification achieved an accuracy of 99.70%, recall of 99.54%, precision of 99.32%, and F-1 score of 99.43% during the test phase. To ensure the reliability of the ViT model's multi-class classification of WBCs, the pixel areas that the model focuses on in its predictions are visualized through the Score-CAM algorithm.

Papillary thyroid cancer (PTC) is commonly characterized by multifocality, which is associated with aggressive features and a less favorable prognosis. The current study aimed to compare the clinicopathologic characteristics and long-term oncological outcomes of bilateral and unilateral multifocal PTC. The medical records of 1745 patients with multifocal PTC who underwent thyroid surgery at Seoul St. Mary’s Hospital were retrospectively reviewed. The clinicopathological characteristics and recurrence rates were compared based on cancer laterality. Further, 357 patients who underwent total thyroidectomy were matched to investigate the recurrence risk and disease-free survival (DFS). Before propensity score matching (PSM), there was no significant difference in the recurrence rate between the bilateral and unilateral multifocal PTC groups. Cancer laterality was not a predictor of DFS based on the Cox regression analyses. However, after PSM, unilateral multifocality was associated with a significantly high risk of recurrence. Similarly, unilateral multifocality was associated with a significantly poor DFS based on the Kaplan–Meier analysis. Compared with bilateral PTC, unilateral multifocal PTC was associated with a poor DFS. A comprehensive preoperative examination should be performed to detect multifocality before the initial surgical intervention for optimal treatment. Postoperative short-term follow-up is recommended for unilateral multifocal PTC for recurrence surveillance.

Healthy eating behaviour of women is critical not only for their health but also for their children's health and well-being. The present study examined the dietary pattern, nutrition knowledge and attitudes of working women in Western Province, Sri Lanka. In addition, identify the factors associated with Dietary Diversity Score (DDS). A cross-sectional study was conducted among 300 working women, aged 20-60 years, in Western Province, Sri Lanka. The data on so-cio-demography, dietary patterns, and nutrition-related knowledge and attitudes were collected. Overall, 38% of the women were overweight and 13% were obese. The median frequency of intake of chicken, fish, eggs, milk and milk products, green leafy vegetables and fruits were 2, 5, 2, 9, 5 and 10 respectively, per week. A large majority of the women (70%) had tea/coffee with sugar and snacks (60%) at least four times a week. Only a third of the women met the minimum DDS, while more than half of the women had good nutrition-related knowledge and attitudes. Multiple regression analysis showed that age and household income were significantly independently related to DDS, while attitudes were negatively associated. While there was a trend, the association of nutrition-related knowledge with DDS was not statistically significant (p=0.057). The overall F ratio (8.46) was highly significant (p=0.000) and the adjusted R2 was 0.093. The results demonstrated that a significant proportion of working women have good basic nutrition-related knowledge and attitudes, while two-thirds of them do not meet the minimum DDS. Furthermore, age, family income and knowledge were positively associated with DDS, while attitudes were negatively associated. Before designing any intervention, further research is needed using a qualitative approach to understand how nutrition knowledge and eating behaviour are related in this population group.

Middle East region experiences a high prevalence of hypovitaminosis D, yet most genetic studies on Vitamin D have focused on European populations. Furthermore, there is a lack of research on the genomic risk factors affecting the elderly population, who are more susceptible to health burden. We investigated the genetic determinants of 25-hydroxyvitamin D levels in elderly Lebanese individuals (n=199) through a whole exome-based genome-wide association study. We identified new loci with suggestive evidence of an association with Vitamin D levels, including rs141064014 in the MGAM gene (P-value of 4.40 × 10−06) and rs7036592 in PHF2 (P-value of 8.43 × 10−06). A meta-analysis of the Lebanese data and the largest European genome-wide association study confirmed consistence replication of numerous variants, including rs2725405 in SLC38A10 (P-value of 3.73 x 10-08). Despite the lower performance of European-derived polygenic risk scores compared to the European estimations, it still effectively predicted Vitamin D deficiency among elderly Lebanese individuals. Our findings provide novel insights into the genetic mechanisms of Vitamin D deficiency in Middle Eastern elderly populations, facilitating the development of personalized approaches for more effective management of hypovitaminosis D. Additionally, we demonstrated that whole exome-based genome-wide association study is an effective method for identifying genetic components associated with phenotypes.

Front-of-pack labelling (FOPL) systems, such as the Nutri-Score, play a crucial role in promoting healthy diets and raising consumer awareness. Our study aimed to gather the opinions of Polish experts on the Nutri-Score and its relation to an ideal information system. We conducted a Poland-wide expert opinion study using a cross-sectional design survey with 75 participants, who had an average of 18±13 years of experience and were mainly employed at medical and agricultural universities. The data were collected with CAWI method. The results showed that the most important features of an FOPL system were clarity, simplicity, consistency with healthy eating recommendations, and the ability to objectively compare products within the same group. While more than half of the respondents believed that the Nutri-Score provides an overall assessment of a product’s nutritional value and facilitates quick purchasing decisions, it falls short in helping consumers compose a balanced diet and cannot be applied to all product groups. The experts also expressed concerns about the system’s ability to account for a product’s degree of processing, full nutritional value and carbon footprint. In conclusion, Poland’s current labelling system needs expansion, but the Nutri-Score requires significant and deep changes and validation against national guidelines and expert expectations before implementation.

Based on the survey data of 5 large grain-producing provinces in China, we studied the promo-tion effect of the agricultural production trusteeship on high quality production of grain by using a propensity score matching method. The empirical results show that the high-quality production of grain level increased by 0.292, with an increase of 87.4% after participating in agricultural production trusteeship. Among them, the level of high efficiency, premiumization, greenization and branding of grain production has respectively increased by 0.234, 0.373, 0.208, and 0.158. However, there are differences in the facilitation effects of different trusteeship services, with the best promotion effect of agricultural material supply services, followed by post-harvest services, and then land management services and cultivating and harvesting services, the ATT is 0.287, 0.230, 0.158, and 0.139, respectively. Meanwhile, there are differences in the promotion effects for farm households with different factor endowments. The promotion effect is better for small farm households with 3 laborers or less, a land management scale of 10 mus or less, and 1 type of ag-ricultural machinery or less. Therefore, in order to give full play to the promotion effect of agri-cultural production trusteeship on high quality production of grain, the government should vigorously support its development and guide more smallholders to choose agricultural produc-tion trusteeship.

Farmers are continually looking for new reliable, objective and non-invasive methods for evaluation of ewe condition. Live weight (LW) and body condition score (BCS) are used by farmers as a basis to determine the condition of the animal. Body composition is an important aspect of monitoring animal condition. The body composition is the amount of fat, lean and bone; knowing the amount of each is important because the information can be used for better strategic management interventions. Experiments were conducted to establish the relationship between body composition and body parameters, at key life’s stages (weaning and pre-mating), using measurements automatically determined by an image processing ap-plication at Lincoln University sheep farm for 88 Coopworth ewes. Computerized Tomography technology was used to develop relationship with body parameters and a subset was used to validate the predicted model. Multivariate linear regression (MLR), artificial neural network (ANNs) and regression tree (RT) statistical analysis methods were evaluated to determine their efficacy to predict body fat, lean and bone. The results showed a correlation between fat, lean and bone determined by CT and the fat, lean, bone weight estimated by live weight and body parameters calculated using the image processing application with R2 values of 0.90 for fat, 0.72 for lean and 0.50 for bone using ANNs statistical model. From these results, farmers can utilize accurate measures of fat which will enhance nutritional and management practices.

This study investigated the effects of modified rice bran arabinoxylan compound (RBAC) as a dietary supplement on the gut microbiota of healthy adults. Ten volunteers supplemented their diet with 1g of RBAC for six weeks and 3g of RBAC for another six weeks, with a three-week washout period. Faecal samples were collected every 3 weeks over 21 weeks. Microbiota from faecal samples were profiled using 16S rRNA sequencing. Assessment of alpha and beta microbiota diversity was performed using the QIIME2 platform. The results revealed that alpha and beta diversity were not associated with the experimental phase, interventional period, RBAC dosage, or time. However, statistical significance of participant was detected in alpha (p&lt;0.002) and beta (weighted unifrac, p=0.001) diversity. Explanatory factors including age and diet were significantly associated with alpha (p&lt;0.05) and beta (p&lt;0.01) diversity. The individual beta diversity of six participants significantly changed (p&lt;0.05) during the interventional period. Seven participants showed statistically significant taxonomic changes (ANCOM W≥5). These results classified four participants as responders to RBAC supplementation, with a further two participants likely responders. In conclusion, the gut microbiome is highly individualised and modulated by RBAC as a dietary supplement, dependent on lifestyle and dietary intake

In various countries of the global south, school feeding programs are implemented in order to alleviate short-time hunger in children, improved their nutrition and provide employment for food vendors. The impact of these programs is important not only in terms of pupils’ nutrition but also in improving farmers’ livelihoods. This study analyzes the impact of the school feeding program on smallholders' food security based on data collected in 2021 from 240 farmers surveyed in northeast Nigeria. Differently from other studies, several econometric methods are used to analyze the data, namely, binary probit regression, propensity score matching, inverse probability weighted adjusted regression and endogenous switching regression. The results show that about 40% of the beneficial smallholder farmers are food secure compared to 20% of the non-beneficiary households. Findings revealed that the Homegrown school feeding program (HGSF) positively improved smallholder farmers improve household food security status. Results provide evidence for the need to expand school feeding programs vis-a-vis interventions in facilitating farmers’ access to capital and capacity building for better integration in the supply chain.

To examine the association of clinical, treatment, and dose parameters with late urinary toxicity after low-dose-rate brachytherapy (LDR-BT) for prostate cancer, we retrospectively studied patients with prostate cancer who underwent LDR-BT from January 2007 through December 2016. Urinary toxicity was assessed using the International Prostate Symptom Score (IPSS) and Overactive Bladder (OAB) Symptom Score (OABSS). Severe and moderate lower urinary tract symptoms (LUTS) were defined as IPSS ≥ 20 and ≥ 8, respectively; OAB was defined as a nocturnal frequency of ≥ 2 and a total OABSS of ≥ 3. In total, 203 patients (median age, 66 years) were included, with a mean follow-up of 8.4 years after treatment. The IPSS and OABSS worsened after 3 months of treatment; these scores improved to pretreatment levels after 18–36 months in most patients. Patients with a higher baseline IPSS and OABSS had a lower frequency of moderate and severe LUTS and OAB at 24 and 60 months, respectively. LUTS and OAB at 24 and 60 months were not correlated with the dosimetric factors of LDR-BT. Although the rate of long-term urinary toxicities assessed using IPSS and OABSS was low, the baseline scores were related to long-term function. Refining patient selection may further reduce long-term urinary toxicity.

In this work, a series of compounds in the CaO-½Er2O3-CoOz ternary oxide system were synthesized in air at 885℃ using high temperature solid-phase synthesis method. Phase boundary of each solid solution region in the CaO-½Er2O3-CoOz system was determined by X-ray powder diffraction technique. The phase diagram of the CaO-½Er2O3-CoOz system at 885℃ includes three series of ternary oxide solid solutions : (Ca3-xErx)Co4O9-z (0≤x≤0.9), (Ca3-xErx)Co2O6-z (0≤x≤1.25) and (Er1-xCax)CoO3-z (0≤x≤0.33). Four three-phase regions and five solid solution tie-line regions were obtained. The structure of perovskite solid solution (Ca3-xErx)Co2O6-z has been analyzed by Rietveld refinements. With the increase of Er content, the cell parameters of (Ca3-xErx)Co2O6-z exhibit an decreasing trend in a and b directions and an increasing trend in c direction.

Introduction: The choice of Cardiac Preservation Solution (CPS) for myocardial protection at the time of heart procurement remains controversial and uncertainties persist regarding its effect on the early and midterm Heart Transplantation (HTx) outcomes. Thus, we retrospectively analyzed our adult HTx performed with two different CPS, during a period of 12 years, in terms of hospital mortality, mid-term survival, inotropic score, primary graft dysfunction and rejection score. Methods: From January 2009 to December 2020, 154 adult HT were performed in our hospital. Patients were divided in two groups according to the CPS used: St. Thomas (n=75, group P 1) and HTK-Custodiol (n=79, group P 2). The choice of CPS was related to an institutional policy; from 2009 to 2015, St. Thomas solution was exclusively used, and after that, HTK-Custodiol alone. Results: There was no significant difference between the two groups in terms of preoperative and intraoperative features. Postoperatively, the Custodiol group showed significantly lower inotropic score (p&lt;0.0001), mean rejection score (p= 0.036) and 30 days mortality (p=0.0068). The use of HTK-Custodiol was the only variable that improved midterm survival (HTK-Custodiol vs St Thomas, HR= 0.20 (95% CI: 0.069 -0.6) p=0.0039). Conclusion: In our single center experience, using HTK-Custodiol as myocardial protection during heart procurement leads to improved outcomes after HTx, including postoperative inotropic score, rejection score, 30-days mortality and midterm survival.

In this paper, a fuzzy logic-based energy management system and multi-port quasi-z-source converter are proposed that utilizes hybrid renewable energy sources. The system ensures that each energy source module can be used individually by employing fuzzy logic to define power modes. This approach also helps prevent switching losses resulting from extra switching of the source modules. Also, the proposed energy management does not have a mathematical model, so applicability is simple and it is suitable for different multiple input topologies. The Mamdani fuzzy inference system can be designed to capture the nonlinear behavior of the system because of the linguistic rules. Moreover, by adopting the quasi-z-source network to the end of the multi-port converter, the switching losses of the multi-port modules have been significantly reduced. The simulation results are obtained using MATLAB Simulink, and the experimental results are obtained by connecting the circuit to MATLAB Simulink via an Arduino Due.

Background: Current prostate cancer evaluation can be inaccurate and burdensome. Quantitative evaluation of MRI sequences non-invasively helps prostate tumor assessment. However, including Dynamic Contrast Enhancement in the examined MRI sequence set can add complications, inducing possible side effects from the IV placement or injected contrast material, and prolongs scanning time. Purpose: Predict the risk of developing Clinically Significant (Insignificant) prostate cancer CsPCa (CiPCa) and International Society of Urologic Pathology (ISUP) grade using processed Signal to Clutter Ratio (SCR) derived from spatially registered bi-parametric MRI (SRBP-MRI) and thereby enhance non-invasively management of prostate cancer. Methods: This pilot study retrospectively analyzed 42 consecutive prostate cancer patients from the PI-CAI data collection. BP-MRI (Apparent Diffusion Coefficient, High B-value, T2) were resized, translated, cropped, and stitched to form spatially registered SRBP-MRI. Efficacy of noise reduction was tested by regularizing, eliminating principal components (PC), and minimizing elliptical volume from the covariance matrix to optimize the SCR. MRI guided biopsy (MRBx), Systematic Biopsy (SysBx), combination (MRBx+SysBx), or radical prostatectomy determined the ISUP grade for each patient. ISUP grade >=2 (<2) was judged as CsPCa (CiPCa). Linear and Logistic regression were fitted to ISUP grade and CsPCa/CiPCa SCR. Correlation Coefficients (R) and Area Under the Curves (AUC) for Receiver Operator Curves (ROC) evaluated the performance. Results: High correlation coefficients (R) (>0.55) and high AUC (=1.0) for linear and/or logistic fit from processed SCR and z-score for SRBP-MRI greatly exceed fits using prostate serum antigen, prostate volume, and patient age (R~0.17). Patients assessed with combined MRBx+SysBx and from individual MRI scanners achieved higher R (R=0.207+/-0.118) than using all patients in the fits. Conclusions: In the first study to date to apply and test hyperspectral approaches for assessing tumor aggressiveness on SRBP-MRI, high values of R and exceptional AUC to fit the ISUP grade and CsPCA/CiPCA were comparable or better than those from artificial intelligence in other studies.

Invasive fungal infections, notably candidemia, have been associated with COVID-19. The epidemiology of candidemia has significantly changed during the COVID-19 pandemic. We aim to identify the microbiological profile, resistance rates, and outcomes of COVID-19 associated candidemia (CAC) compared to patients with candidemia not associated with COVID-19. We retrospectively collected data on patients with candidemia admitted to the American University of Beirut Medical Center between 2004 and 2022. We compared the epidemiology of candidemia during and prior to the COVID-19 pandemic. Additionally, we compared the outcomes of critically ill patients with CAC to those with candidemia without COVID-19 from March 2020 till March 2022. Among 245 candidemia episodes, 156 occurred prior to the pandemic and 89 during the pandemic. Of the latter, 39 (43.8%) were CAC, most of which (82%) were reported from intensive care units (ICU). Non-albicans Candida (NAC) spp. were predominant throughout the study period (67.7%). Candida auris infection was the most common cause of NAC spp. in CAC. C. glabrata had decreased susceptibility rates to fluconazole and caspofungin during the pandemic period (46.1% and 38.4% respectively). Mortality rate in the overall ICU population during the pandemic was 76.6%, much higher than the previously reported mortality of candidemia from previous studies at our center. There was no significant difference in 30-day mortality between CAC and non-CAC (75.0% vs 78.1%; P =0.76). Performing ophthalmic examination (P = 0.002), CVC removal during the 48 hours following the candidemia (P = 0.008) and identifying the Candida spp. (P = 0.028) were significantly associated with a lower case-fatality rate. The epidemiology of candidemia has been significantly affected by the COVID-19 pandemic at our center. Rigorous infection control measures and proper antifungal stewardship are essential to combat highly resistant species like C. auris.

Cyclic olefin copolymer (COC) is a novel type of thermoplastic polymer gaining the attention of the scientific community in electronic, optoelectronic, biomedicine and packaging applications. Despite the benefits in the use of COC like undoubted optical transparency, chemical stability, good water-vapor barrier and biocompatibility, its original hydrophobicity restricts its wider applicability and optimization of its performances. Presently, we report on the optical, and morphological properties of the films of COC covered with Ti in selected areas. The layer of Ti on COC was deposited by pulsed lased deposition processing. The Ti/COC film was characterized by UV-Vis spectroscopy indicating that its transmittance in the visible region decreased by about 20% with respect to the pristine polymer. The quality of the deposited Ti was assessed with the morphology by scanning electron (SEM) and atomic force microscopies (AFM). The modification of the wettability was observed by the sessile drop method indicating a reduction of the native hydrophilicity.

: This study investigates the use of various thunderstorm indices in predicting severe thunderstorms events during the monsoon season in four different regions in India. The research evaluates the performance of the prediction model using a model skill score and utilizes the Weather Research and Forecasting (WRF) model with the double moment microphysics scheme to simulate model cases. It also compares fifteen thunderstorm indices derived from the ERA5 dataset to identify the most effective index for predicting severe thunderstorms events. The results of this study show that in-corporating thunderstorm indices with model skill scores improves severe thunderstorms fore-casting in the monsoon season in India. The result revealed that determining the optimal threshold for each index is crucial in achieving accurate predictions. The study also highlights the importance of considering multiple indices rather than relying on a single index to predict severe thunderstorms events. The advance indices such as Energy Helicity Index (EHI), Supercell Composite Parameter (SCP), mainly works well with extreme severe thunderstorms. The simplistic indices can predict the weak or severe thunderstorm easily. The use of multiple thunderstorm indices can also help mete-orologists to make more accurate predictions, which can further enhance public safety. In conclu-sion, this study demonstrates the potential of incorporating thunderstorm indices with model skill scores like HSS and TSS and combinations of different skill scores in severe thunderstorms fore-casting during the monsoon season in India. Future research can build upon the findings of this study to develop more accurate and reliable severe weather forecasting models.

Broadband reverse saturable absorption is systematically investigated via Z-scan, transient absorption spectrum (TAS). The excited state absorption and negative refraction of Orange IV are observed in the Z-scan experiment at 532 nm. Meanwhile, two-photon induced excited-state absorption and pure two-photon absorption are observed at 600 nm and 700 nm with the pulse width of 190 fs, respectively. An ultrafast broadband absorption in visible wavelength region is observed via TAS. The different nonlinear absorption mechanism at multiple wavelengths is discussed and interpreted from the results of TAS. In addition, the ultrafast dynamics of negative refraction in the excited state of Orange IV is investigated via degenerate phase object pump probe, from which the weak long-lived excited state is extracted. All studies indicate that Orange IV has the potential to be further optimized into a superior broadband reverse saturable absorption material and also has certain reference significance for the study of optical nonlinearity in organic molecules containing azobenzene groups.

Background: Malnutrition in critically ill paitents is closely linked with clinical outcomes. During acute inflammatory states, nutrition cannot reverse the loss of body cell mass completely. Studies on nutritional screening and strategy considering metabolic changes not yet been conducted. We aimed to identify nutrition strategies using the modified Nutrition Risk in the Critically ill (mNUTIRC) score. Methods: Nutrition support data, laboratory nutrition indicators, and prognosis indices were prospectively collected on the 2nd and 7th day after admission. It is to identify the effect of changes on the metabolic status and critical target of nutrition intervention. To discriminate the high-risk group of malnutrition, receiver operating characteristic curves were plotted. Risk factors associated with 28 day-mortality were evaluated using multivariable Cox proportional hazards regression. Results: A total of 490 and 266 patients were analyzed on the 2nd and 7th day, respectively. Only the mNUTRIC score showed significant differences in nutritional risk stratification. The use of vasopressors, hypo-protein supply (< 1.0 g/kg/day), high mNUTRIC score and hypoalbuminemia (<2.5 mg/dl) in the recovery phase was strongly associated with 28-day mortality. Conclusions: The implementation of the mNUTRIC score and protein supply in the post-acute phase is critical to improve 28-day mortality in critically ill patients.

The difficulty in detecting tumors in earlier stages is the major cause of mortalities of patients, despite the advancements in treatment and research regarding ovarian cancer. Deep Learning algorithms are applied to serve the purpose of a diagnostic tool by applying them on CT scan images of the ovarian region. The images go through a series of pre-processing techniques and further the tumor is segmented using the UNet model. Instances are then classified into two categories – benign and malignant tumors. Classification is performed using Deep Learning models like CNN, ResNet, DenseNet, Inception-ResNet, VGG16 and Xception along with Machine Learning models such as Random Forest, Gradient Boosting, AdaBoosting, XGBoosting. DenseNet 121 emerges as the best model on this dataset even after applying optimization on the Machine Learning models by obtaining an accuracy of 95.7%. The current work demonstrates the comparison of multiple CNN architectures among themselves and with common Machine Learning algorithms, with and without optimization techniques applied.

The gravitational constant is an unchanging quantity included in the law of universal gravitation. The value of this constant is known much less accurately than other fundamental physical constants, which is due to the experimental difficulties of measuring it. Here we report a simple method for the theoretical calculation of the gravitational constant using the elementary charge, speed of light, Z boson mass, and relativistic mechanics.

As one of the world's most populous countries, Indonesia is struggling with the composition of its people, the majority of whom are unemployed productive-age individuals with low education levels. Another issue is the high poverty rate, which is followed by issues of gender inequality. The government cannot solve these social issues on its own. There is a need for community support to solve these problems through sustainable social entrepreneurship activities. Using the Theory of Planned Behavior and Outcome Expectation, this study will determine the factors that influence the interest of individuals known as the Z and Millennial generation, aged 18 to 34 years old, in becoming social entrepreneurs. This study applied a quantitative approach with a judgmental sampling technique to a sample of Generation Z and Millennials who have ever participated in social activities but have not yet started their own business. The study gathered 210 respondents, who were then analyzed using the PLS-SEM method with multiple group analysis generation-based comparison. According to the findings, the Millennial Generation's Attitude Toward Behavior, Subjective Norms, and Outcome Expectation all had a positive impact on Social Entrepreneurial Intention. Meanwhile, Subjective Norms had no effect on Social Entrepreneurial Intention in the Z Generation. Only attitude toward behavior, perceived behavioral control, and outcome expectation have a positive effect on the development of social entrepreneurial intentions. Furthermore, the findings of this study confirm that subjective norms influence attitude toward behavior and Perceived Behavioral Control in both Generation Z and millennials.

Introduction. The main task of the study was to measure the workload of nurses in the care of a patient with a developmental defect–congenital diaphragmatic hernia (CDH)–in the neonatal intensive care unit, which was evaluated on the basis of standardized tools Therapeutic Intervention Scoring System (TISS–28), Nine Equivalents of Nursing Manpower use Score (NEMS) and Nursing activities Score (NAS). Methods. Retrospective study. The workload was measured using TISS–28, NEMS and NAS tools. Descriptive statistics were used to analyze the data, and a single-sample test was used to verify the research hypotheses. Results. The sample consisted of medical records of 33 patients; 592 observations were analyzed. Studies prove the need for research on the workload of nurses in neonatal intensive care units. A patient with CDH should receive nursing care as required. Conclusion. It is necessary to implement a model for measuring the workload of nurses in neonatal intensive care units, taking into account the evaluation of work and its optimization.

The Impact of Event Scale-Revised (IES-R) is the most popular measure of post-traumatic stress disorder (PTSD), which has been recently validated in Arabic. This instrumental study aimed to determine optimal cutoff scores of the IES-R and its subscales in Arab samples of psychiatric patients (N = 168, 70.8% females) and healthy adults (N = 992, 62.7% females) from Saudi Arabia during the COVID-19 pandemic as an ongoing collective traumatic event. Based on a cutoff score of 14 of the Depression Anxiety Stress Scale 8-items (DASS-8), receiver operator curve (ROC) analysis revealed two optimal points of 39.5 and 30.5 for the IES-R in the samples (area under the curve (AUC) = 0.86 &amp; 0.91, p values = 0.001, 95% CI: 0.80-0.92 &amp; 0.87 to 0.94, sensitivity = 0.85 &amp; 0.87, specificity = 0.73 &amp; 0.83, Youden index = 0.58 &amp; 0.70, respectively). Different cutoffs were detected for the six subscales of the IES-R, with numbing and avoidance expressing the lowest predictivity for distress. Meanwhile, hyperarousal followed by the irritability expressed stronger predictive capacity for distress than all subscales in both samples. In path analysis, pandemic-related irritability resulted from direct and indirect effects of key PTSD symptoms (intrusion, hyperarousal, and numbing). Irritability contributed to traumatic symptoms of sleep disturbance in both samples while the opposite was not true. The findings suggest usefulness of the IES-R at a score of 30.5 for detecting adults prone to trauma related distress, with higher scores needed for screening in psychiatric patients. Various PTSD symptoms may induce dysphoric mood, which represents a considerable burden that may induce circadian misalignment and more noxious psychiatric problems/ co-morbidities (sleep disturbance) in both healthy and diseased groups.

Background: Osteoarthritis is the most common degenerative joint disease resulting in pain and altered joint function. Objective: We investigated the possible association between serum interleukin-6 and symptoms of knee osteoarthritis with regard to pain, stiffness, physical function, assessed by the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). We also examined the connections between serum interleukin-6 and radiographic severity in primary knee osteoarthritis patients. Methods: In this case-control study, fifty primary knee osteoarthritis patients and fifty age and sex matched controls were randomly recruited. Serum interleukin-6 levels were immunoassayed in patients’ and controls’ serum. Patients’ knee pain, stiffness and physical function were assessed by the respective subscales of the WOMAC Index. Standing anteroposterior radiographs of the knee joint were performed and graded with the Kellegren-Lawrence grade. Results: The mean serum IL-6 level was significantly higher in osteoarthritis patients (110.22 ± 46.98pg/ml) than controls (46.04 ± 12.34 pg/ml) (p=0.001). The WOMAC Index in patients ranged from 0 – 95 and the Kellegren-Lawrence score mean was 2.7 ± 0.76. There was a significant correlation between serum IL-6 levels and pain (r=0.595 p=0.001), physical function score (r=0.666, p=0.001)), and the radiographic score (r=0.799, p=0.001). Regression analysis showed that IL-6 level had a greater impact on both the WOMAC Index (p=0.005) and the Kellegren-Lawrence score (p=0.01). Conclusion: Serum IL-6 level is increased in primary knee osteoarthritis patients. Also, serum interlukin-6 is significantly related to osteoarthritis symptoms and radiographic severity.

Chemotherapy for lung cancer has made remarkable progress, and its selection has been subdivided by genetic analysis. Although response evaluation criteria in solid tumors (RECIST) is a simple and highly objective evaluation method, it has been pointed out that it has the disadvantage of not being able to accurately evaluate the therapeutic effect of molecularly targeted drugs and immune checkpoint inhibitors. The purpose of this study is to determine whether quantitative evaluation of DWIBS is useful in determining the effectiveness of treatment for lung cancer. There were 31 patients with lung cancer and 56 patterns were obtained. First, the determination of treatment effect (PD, SD, PR) based on RECIST was performed on CT. Second, tDV and ADC (median) were measured using BD score from DWI images taken at the same time, and the rate of change was calculated. Then, we compared and examined the correlation between RECIST and the rate of change in tDV. There were correlations between RECIST and the rate of change in tDV in PD and PR cases respectively. Compared RECIST on CT, DWIBS using BD score would be more accurate for response evaluation of treatment. There was a tendency that tDV decreased with increasing ADC values, but some of the cases had a dissociated response with increasing ADC values and increasing tDV. Thus, since the color display of ADC values allows us to infer their contents, it would be useful for the evaluation of cases such as dissociated response and pseudoprogression, which are suspected to be atypical responses that are difficult to evaluate with RECIST and other methods.

This paper estimates the effect of trust in government on rural residents’ contributions in China’s rural pension program using the Propensity Score Matching (PSM) method. We construct an analytical framework for rural residents' decision-making in pension program and provide analysis using data from China Family Panel Studies (CFPS) and 25 provincial Departments of the Human Resources and Social Security (DOHRSS) in China. Our analysis shows that rural residents’ trust in government will influence their contributions to the pension programs by affecting their expected return of the investments. Our results suggest that the government should improve rural residents’ trust in government in order to develop a successful and sustainable rural pension program.

A key step in providing management/treatment options to men with suspected prostate cancer (PCa) is categorizing the risk for the presence of benign, low risk, intermediate risk, or high-risk disease. Our novel modality brings new evidence, based on the long-known hallmark characteristic of PCa – decreased Zinc (Zn), which is the most direct metabolic sign of malignancy and its aggressiveness. To date, this approach has not been adopted for clinical use for a number of reasons that are described in this article and which have been addressed by our approach: Zn has to be measured on fresh samples, prior to fixating in formalin, therefore samples have to be scanned during the biopsy session; as Zn depletion occurs in the glands, where the tumors develop, estimation of the glands’ levels in the scanned tissue along with their compactness, are essential for accurate diagnosis. Combined with the Zn depletion, this facilitates a reliable assessment of the disease aggressiveness. Data gathered in the clinical study described here indicate that in addition to improving the biopsy quality by real-time interactive guidance, a malignancy score can now be established for the entire prostate, allowing higher granularity personalized risk stratification and more decisive treatment decisions for all PCa patients.

Tailoring treatment in patients with Hodgkin lymphoma (HL) is paramount to maximize outcomes while avoiding unnecessary toxicity. We aimed to compare the performance of SUVmax reduction (ΔSUVmax%) versus Deauville score (DS) in assessing chemotherapy response in pediatric HL patients undergoing 18F-FDG PET-CT. Fifty-two patients with biopsy-proven HL (age 8-16 years) were enrolled at baseline, interim (after the 2nd or 3rd chemotherapy round), and post-therapy (upon completion of first-line chemotherapy) 18F-FDG PET-CT. Interim and post-therapy DS and ΔSUVmax% were compared as response predictors. Patients were classified as responders and non-responders based on 24-month clinical follow-up. Interim DS showed a sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and diagnostic accuracy of 100%, 80.4%, 100%, 40% and 82.7%, respectively in predicting response. Post-therapy DS showed a sensitivity, specificity, PPV, NPV and accuracy of 66.7%, 97.8%, 95.7%, 80% and 94.2%. Interim ΔSUVmax% showed a sensitivity, specificity, PPV, NPV and accuracy of 83.3%, 82.6%, 97.4%, 38.5% and 82.7%, with a 56.3% cutoff. Post-therapy ΔSUVmax% showed a sensitivity, specificity, PPV, NPV and accuracy of 83.3%, 84.8%, 97.5%, 41.7% and 84.6%, with a 76.8% cutoff. Sensitivity, specificity (p<0.05) and NPV (p<0.01) were significantly higher using DS than ΔSUVmax%. In conclusion, DS can predict chemotherapy response better than ΔSUVmax% in pediatric HL patients.

Marek’s Disease (MD) has a significant impact on both the global poultry economy and animal welfare. The disease pathology can include neurological damage and tumour formation. Sexual dimorphism in immunity and known higher susceptibility of females to MD makes the chicken Z chromosome (GGZ) a particularly attractive target to study the chicken MD response. Previously, we used a Hy-Line F6 population from a full-sib advanced intercross line to map MD QTL regions (QTLRs) on all chicken autosomes. Here we mapped MD QTLRs on GGZ in the previously utilized F6 population with individual genotypes and phenotypes, and in eight elite commercial egg production lines with daughter-tested sires and selective DNA pooling (SDP). Four MD QTLRs were found from each analysis. Some of these QTLRs overlap regions from previous reports. All QTLRs were tested by indiviuals from the same eight lines used in the SDP and genotyped with markers located within and around the QTLRs. All QTLRs were confirmed. The results exemplify the complexity of MD resistance in chickens and the complex distribution of P-values and LD pattern and their effect on localization of the causative elements. Considering the fragments and interdigitated LD blocks while using LD to aid localization of causative elements, one must look beyond the insignificant markers, for possible distant markers and blocks in high LD with the significant block. The QTLRs found here may explain at least part of the gender differences in MD tolerance, and provide targets for mitigating the effects of MD.